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PS2010

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PS2010 mind map
Jada Khan
Mind Map by Jada Khan, updated more than 1 year ago
Jada Khan
Created by Jada Khan over 7 years ago
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Resource summary

PS2010
  1. SPSS
    1. stats tests
      1. Chi-squared
        1. analyse nominal/frequency/categorical data
          1. nominal data: describes the group a P belongs to
            1. NON-PARAMETRIC
        2. Differences between conditions: COMPARISIONS
          1. ANOVA, t test
            1. t tests
              1. ERRORS
                1. Type 1: THE WORST!!!!!
                  1. Finding effect in sample, accepting H, but NO effect in real life
                    1. Incorrectly finding signif. effect
                    2. Cannot avoid unless testing ENTIRE population! 5% error allowed ALPHA LEVEL (p <.050)
                    3. Type 2
                      1. Found no effect in sample, accept null H, but there ARE effects in real world
                    4. PARAMETRIC ANALYSIS
                      1. Homogeneity of variance
                        1. LEVENE'S TEST
                          1. Not signif.: (p > .050)
                            1. ASSUMPTION HAS BEEN MET
                              1. "equal variances assumed" row
                              2. p GREATER THAN .050
                              3. Signif.: p < .050
                                1. ASSUMPTION HAS BEEN VIOLATED
                                  1. "Equal variances not assumed" row
                                  2. p LESS THAN .050
                            2. Independent t test
                              1. SPSS output
                                1. "Independent samples test"
                                  1. LEVENE'S
                                    1. t (df) = t statistic, p value
                                      1. descriptives
                                        1. Population (N) individual group (n)
                                          1. include M and SD
                                            1. Confidence intervals (CI)
                                              1. CI of a mean: uses N and SD -> lower and upper score
                                                1. Can be 95% certain the upper and lower scores will reflect any sample taken from data set - even if exp is replicated
                                        2. WRITE UP
                                      2. comparing groups
                                        1. "Group stats"
                                        2. Null hypothesis - A = B, no direction stated
                                          1. After analysis - either accept (if p is NS) or reject null hypothesis (p is Sigif.)
                                        3. If SPSS output - p = .000 -> p < .001
                                          1. Null hypothesis - A = B, non directional; easiest H to make if there is no previos research
                                            1. After data analysis - either accept or reject Null H
                                              1. Accept: there is a relationship
                                                1. Reject: there is no relationship
                                        4. Repeated t test
                                          1. SPSS output
                                            1. "Paired samples test"
                                              1. t (df) = t statistic, p value
                                            2. no homogeneity of variance or Levene's test
                                              1. violates assumptions of independence of obs.; random variance (WITHIN groups) is reduced
                                                1. SPHERICITY ASSUMPTION
                                                  1. W = W, x2 (df) = x2, p = p value
                                            3. One sample t test
                                              1. compares data from a single group to a "reference value"
                                                1. eg. population
                                                2. SPSS output
                                                  1. "one sample t test" -> test value (reference)
                                                    1. interpreting direction: is sample M signif higher/lower than test value?
                                              2. ANOVA: Independent measures
                                                1. Analysis of Variance; compares many groups
                                                  1. 3 MAIN ASSUMPTIONS
                                                    1. normal distribution of DV
                                                      1. homogeneity of variances
                                                        1. LEVENE'S
                                                        2. independence of observations
                                                        3. SPSS OUTPUT
                                                          1. "Between subjects factors" + "descriptives"
                                                            1. "Levene's test of equality of error variances"
                                                              1. F (df1, df2) = F ratio, p = p value
                                                                1. if Levene's is NS (p > .050)
                                                                  1. GOOD - Assumption has been met
                                                                    1. Bonferroni
                                                                      1. (few pairwise comparisons)
                                                                        1. adjusts alpha level: .050 / no. of conditions
                                                                        2. Tukey
                                                                          1. (many pairwise comparisons)
                                                                      2. Levene's = signif (p < .050)
                                                                        1. BAD - Assumption has been violated
                                                                          1. Games-Howell
                                                                      3. "Tests of bet. subjects effects"
                                                                        1. F (model df, error df) = F ratio, p = p value
                                                                          1. eg. if IV = time, DV = no. words recalled -> main effect of time is reflected through this write up
                                                                            1. write up
                                                                              1. explain analysis used
                                                                                1. has asumption of homogeneity been met?
                                                                                  1. report and interpret dirction of main effect
                                                                          2. "Source" error = random variance
                                                                            1. "mean square" time: explained V; error: random V
                                                                              1. big F ratio = likely signif !!!
                                                                  2. Preferred to multiple t tests because...
                                                                    1. eg. w/ two t tests = 5% error x 2 = 10% error
                                                                      1. increased chance of making a Type 1 error w/ multiple t tests
                                                                        1. Familywise error: making one or more type 1 errors
                                                                        2. F ratio: ratio of explained (experimental) to random variance
                                                                          1. Exp / random
                                                                        3. ANOVA: Repeated measures
                                                                          1. directional H - planned contrasts
                                                                            1. non-directional H - post hocs are limited for rep. anova
                                                                              1. use bonferroni
                                                                            2. SPSS
                                                                              1. (don't need to look at "multivariate tests") !
                                                                                1. "within sub. factors" - coding variables for contrast interpretation
                                                                                  1. descriptives
                                                                                    1. Mauchly's test of sphericity
                                                                                      1. if NS: assumption of sphericty has not been violated
                                                                                        1. "sphericity assumed" rows - main effect stats
                                                                                        2. is S: sphericity been violated
                                                                                          1. GREENHOUSE GEISER (alters df)
                                                                                          2. W = Mauchly's W, X2 (df) = Chi squared value, p = sig.
                                                                                    2. Repeated measures ANCOVA
                                                                                      1. EMM's rather than descriptives
                                                                                        1. Mauchly's
                                                                                          1. Confound: F (covariate df, error df) = F ratio, p = sig.
                                                                                            1. IV * confound interaction row can be ignored in SPSS output (usually NS)
                                                                                              1. "tests of within subjects contrasts" - ignore interaction and error rows
                                                                                            2. G-G if Mauchly's is S
                                                                                        2. Two-way repeated ANOVA
                                                                                          1. Two-way Mixed ANOVA
                                                                                            1. 1 (or more) IV that has independent p's+ 1 (or more) IV that has repeated p's
                                                                                              1. eg. examining whether the importance of looks (IV1) differs for males and females (IV2). DV: likeliness of going on 2nd date
                                                                                                1. SPHERICITY: repeated IV
                                                                                                  1. LEVENE'S: independent IV
                                                                                                    1. interpreting main effect + interaction - MEANS and plots
                                                                                                      1. break down interaction: split file for either looks / gender; repeated ANOVA
                                                                                              2. Three-way mixed ANOVA
                                                                                                1. 3 IV's - independent and repeated measures
                                                                                                  1. if there are only 2 levels of each IV - ASSUME SPHERICITY
                                                                                                    1. EMM'S for interpretation
                                                                                                      1. IV1 main effect
                                                                                                        1. IV2 main effect
                                                                                                          1. IV3 main effect
                                                                                                            1. Interaction effects
                                                                                                              1. break down w/ split file
                                                                                                    2. effects of indep. and repeated V's are presented in diff parts of output !
                                                                                                    3. 2 IV's: same p's in different conditions of each IV
                                                                                                      1. eg. examining whether looks (IV1) and personality (IV2) have an effect on attractiveness (DV)
                                                                                                        1. SPHERICITY
                                                                                                          1. W = Mauchly's W, X2 (df) = Chi squared value, p = sig.
                                                                                                  2. ANCOVA
                                                                                                    1. takes into account a covariate (variance caused by confound)
                                                                                                      1. when analysisng a covariate - could explain some of the random variance
                                                                                                        1. SPSS
                                                                                                          1. EMM's
                                                                                                            1. adjusted using covariate
                                                                                                              1. interpreting output requires EMM''s rather than unadjusted descriptives
                                                                                                            2. "tests of between subjects effects"
                                                                                                              1. will display 2 results above "error": first will be the covariate, second will be the IV
                                                                                                              2. was homogeneity of variance met? was the covariate S? was the main effect S?
                                                                                                              3. covariate must be continuous and binary
                                                                                                            3. Stage 1
                                                                                                              1. does the covariate explain a signif amount of variability in the DV
                                                                                                                1. Stage 2
                                                                                                                  1. after controlling for the covariate, is there more exp V than random V?
                                                                                                                    1. more random V than exp V: ANOVA NS
                                                                                                                      1. covariate explains small amount of random V: covariate NS
                                                                                                                        1. thus, ANCOVA will be NS
                                                                                                                      2. more random V than exp V: ANOVA NS
                                                                                                                        1. covariate explains a lot of the random V: covariate S
                                                                                                                          1. more exp V than random V: ANCOVA is S
                                                                                                                2. Factorial independent ANOVA
                                                                                                                  1. two-way: 2 variables / factors
                                                                                                                    1. different p's in each cond.
                                                                                                                      1. eg. sex and alcohol consumption (IVs) on aggressiveness (DV)
                                                                                                                      2. examines main effects (effect of each factor on its own) AND interactions between the factors
                                                                                                                        1. break down MAIN EFFECTS if 3+ cond.'s
                                                                                                                          1. line graph /plots reveal significance if:
                                                                                                                            1. lines are not parallel (going in diff directions) - but S depends on angle!
                                                                                                                              1. lines are crossing
                                                                                                                              2. 2 conditions only need to report MEANS "estimates"
                                                                                                                              3. breaking down interaction effect
                                                                                                                                1. separate independent t tests for each level of IV1 to compare to IV2
                                                                                                                                  1. "independent samples t test"
                                                                                                                              4. factorial ANOVA vs one-way ANOVA
                                                                                                                                1. ADVANTAGES
                                                                                                                                  1. analysing interaction effects
                                                                                                                                    1. adding variables reduces error term - accounting for random variance
                                                                                                                                  2. SPSS output
                                                                                                                                    1. LEVENE'S
                                                                                                                                      1. "tests of between subjects effects"
                                                                                                                                        1. "source" - IV1, IV2, IV1 * IV2
                                                                                                                                      2. "multiple comparisons" - post hoc output
                                                                                                                                2. Relationships between variables
                                                                                                                                  1. Correlation, regression
                                                                                                                                    1. Complex correlations
                                                                                                                                      1. Partial correlations
                                                                                                                                        1. PEARSON'S r
                                                                                                                                          1. r values range from perfect negative (-1) - perfect positive (+1)
                                                                                                                                            1. line of best fit - represents DIRECTION of relationship
                                                                                                                                              1. residuals: diff betw. raw data point and line of best fit
                                                                                                                                                1. smaller residuals - more accurate model - line of best fit reduces random variability
                                                                                                                                          2. OUTPUT
                                                                                                                                            1. "CORRELATIONS": R VALUE, P VALUE, N
                                                                                                                                              1. r = .660 POSITIVE relationship
                                                                                                                                                1. r = -1.03 NEGATIVE relationship
                                                                                                                                            2. correlation does not imply causation
                                                                                                                                            3. Multiple regression
                                                                                                                                              1. Complex regression models
                                                                                                                                                1. assumptions
                                                                                                                                                  1. 4
                                                                                                                                                    1. multicollinearity
                                                                                                                                                      1. distribution of residuals
                                                                                                                                                        1. homeoscedacity
                                                                                                                                                          1. outlier effects
                                                                                                                                                          2. Categorical variables in regression
                                                                                                                                                            1. beyond simple correlations: analysing 2 + CONTINUOUS variables
                                                                                                                                                              1. PREDICTIVE MODELS
                                                                                                                                                                1. outcome variable
                                                                                                                                                                  1. predictor variable
                                                                                                                                                                    1. "IVs"
                                                                                                                                                                    2. "DV"
                                                                                                                                                                2. OUTPUT
                                                                                                                                                                  1. PEARSON'S r
                                                                                                                                                                    1. R2 and adjusted R2
                                                                                                                                                                      1. explained variance in outcome V by predictor V
                                                                                                                                                                3. Factor and reliability analysis
                                                                                                                                                                4. Advanced stats
                                                                                                                                                                  1. effect size
                                                                                                                                                                    1. power analysis
                                                                                                                                                                  2. BASICS
                                                                                                                                                                    1. Data view: enter data
                                                                                                                                                                      1. Variable view: define variable properties
                                                                                                                                                                        1. Decide if variable is a continuous score or categorical definition
                                                                                                                                                                          1. Continuous data (always changing/ not fixed; IQ, age) : just enter raw data
                                                                                                                                                                            1. Measure: SCALE
                                                                                                                                                                            2. Categorical data (fixed; sex): needs to be coded
                                                                                                                                                                              1. Measure: NOMINAL
                                                                                                                                                                              2. Before analysis: list, name all variables + demographics
                                                                                                                                                                              3. Row represents one variable
                                                                                                                                                                                1. For catergorical, define VALUES and MEASURE
                                                                                                                                                                                2. Row (across) - participant data
                                                                                                                                                                                  1. Column (down) - variable
                                                                                                                                                                                3. Planned contrasts
                                                                                                                                                                                  1. based off directional H
                                                                                                                                                                                    1. one-tailed
                                                                                                                                                                                    2. DEVIATION
                                                                                                                                                                                      1. Contrast 1
                                                                                                                                                                                        1. 2 vs 1,2,3,4 etc
                                                                                                                                                                                        2. Contrast 2
                                                                                                                                                                                          1. 3 vs 1,2,3,4
                                                                                                                                                                                          2. Contrast 3
                                                                                                                                                                                            1. 4 vs 1,2,3,4
                                                                                                                                                                                            2. compares effect of each cond. (except 1st) with overall effect
                                                                                                                                                                                            3. SIMPLE
                                                                                                                                                                                              1. compares effect of each cond. to 1st (reference)
                                                                                                                                                                                                1. Contrast 1
                                                                                                                                                                                                  1. Contrast 2
                                                                                                                                                                                                    1. Contrast 3
                                                                                                                                                                                                      1. 1 vs 4
                                                                                                                                                                                                      2. 1 vs 3
                                                                                                                                                                                                      3. 1 vs 2
                                                                                                                                                                                                    2. DIFFERENCE
                                                                                                                                                                                                      1. compares effect of each cond. to overall effect of previous cond's
                                                                                                                                                                                                        1. Contrast 1
                                                                                                                                                                                                          1. Contrast 2
                                                                                                                                                                                                            1. Contrast 3
                                                                                                                                                                                                              1. 2 vs 1
                                                                                                                                                                                                              2. 3 vs 2,1
                                                                                                                                                                                                              3. 4 vs 3,2,1
                                                                                                                                                                                                              4. opposite to HELMERT
                                                                                                                                                                                                              5. HELMERT
                                                                                                                                                                                                                1. compares effect of each cond. to all following cond's
                                                                                                                                                                                                                  1. Contrast 1
                                                                                                                                                                                                                    1. Contrast 2
                                                                                                                                                                                                                      1. Contrast 3
                                                                                                                                                                                                                        1. 3 vs 4
                                                                                                                                                                                                                        2. 2 vs 3,4
                                                                                                                                                                                                                        3. 1 vs 2,3,4
                                                                                                                                                                                                                        4. opposite to DIFFERENCE
                                                                                                                                                                                                                        5. REPEATED
                                                                                                                                                                                                                          1. compares effect of each cond. to the next cond. only (not all following cond's)
                                                                                                                                                                                                                            1. Contrast 1
                                                                                                                                                                                                                              1. Contrast 2
                                                                                                                                                                                                                                1. Contrast 3
                                                                                                                                                                                                                                  1. 3 vs 4
                                                                                                                                                                                                                                  2. 2 vs 3
                                                                                                                                                                                                                                  3. 1 vs 2
                                                                                                                                                                                                                                2. 6
                                                                                                                                                                                                                                  1. no. of conditions - 1 = no. of contrasts
                                                                                                                                                                                                                                    1. POLYNOMIAL
                                                                                                                                                                                                                                      1. looks at patterns in data
                                                                                                                                                                                                                                        1. trend analysis only appropriate for continuous IV's !
                                                                                                                                                                                                                                        2. Linear trend
                                                                                                                                                                                                                                          1. Quadratic trend
                                                                                                                                                                                                                                            1. Cubic trend
                                                                                                                                                                                                                                              1. 2 changes in direction
                                                                                                                                                                                                                                              2. 1 change in direction
                                                                                                                                                                                                                                              3. straight line
                                                                                                                                                                                                                                          2. Post-Hoc
                                                                                                                                                                                                                                            1. based off non-directional H
                                                                                                                                                                                                                                              1. two-tailed
                                                                                                                                                                                                                                          3. Descriptive stats
                                                                                                                                                                                                                                            1. Measures of central tendency
                                                                                                                                                                                                                                              1. Mode, median, mean
                                                                                                                                                                                                                                              2. Dispersion
                                                                                                                                                                                                                                                1. Range, variance, SD
                                                                                                                                                                                                                                                  1. Experimental variance: variability between conditions
                                                                                                                                                                                                                                                    1. experimental manipulation
                                                                                                                                                                                                                                                      1. GOOD: likely significaant
                                                                                                                                                                                                                                                        1. large F ratio - significant
                                                                                                                                                                                                                                                          1. explained by more exp variance compared to random variance
                                                                                                                                                                                                                                                        2. Random variance: variability within conditions
                                                                                                                                                                                                                                                          1. measurement/ human error
                                                                                                                                                                                                                                                            1. Indiv. diffs.
                                                                                                                                                                                                                                                              1. unaccounted for/ unmeasured varaibles
                                                                                                                                                                                                                                                                1. BAD: not likely to be significant
                                                                                                                                                                                                                                                          2. Inferential stats: tell us if data is signif. or not
                                                                                                                                                                                                                                                            1. PARAMETRIC
                                                                                                                                                                                                                                                              1. 4 assumptions
                                                                                                                                                                                                                                                                1. Interval / ratio data
                                                                                                                                                                                                                                                                  1. interval: - values possible
                                                                                                                                                                                                                                                                    1. ratio: - values not possible
                                                                                                                                                                                                                                                                    2. normal data distribution
                                                                                                                                                                                                                                                                      1. Independence of observations
                                                                                                                                                                                                                                                                        1. responses from P's (observations) should not be influenced by each other
                                                                                                                                                                                                                                                                        2. Homogeneity of variance
                                                                                                                                                                                                                                                                          1. "SAME" pattern of variance in all groups
                                                                                                                                                                                                                                                                            1. Positively skewed: tail in + direction (right)
                                                                                                                                                                                                                                                                              1. Negatively skewed: tail in - (left)
                                                                                                                                                                                                                                                                                1. HIGH scores over-represented
                                                                                                                                                                                                                                                                                2. LOW scores over-represented
                                                                                                                                                                                                                                                                                3. Ideal because we need to be confident of the mean differences
                                                                                                                                                                                                                                                                            2. NON-PARAMETRIC STATS
                                                                                                                                                                                                                                                                              1. No normal distribution needed!
                                                                                                                                                                                                                                                                                1. No homogeneity of variance needed
                                                                                                                                                                                                                                                                                  1. RANKING DATA
                                                                                                                                                                                                                                                                                    1. SPSS analysis is based around RANKS rather than actual data
                                                                                                                                                                                                                                                                                      1. report MEDIANS! ("statistics")
                                                                                                                                                                                                                                                                                2. Independent
                                                                                                                                                                                                                                                                                  1. 2 conditions
                                                                                                                                                                                                                                                                                    1. Mann-Whitney / Wilcoxon Rank-Sum
                                                                                                                                                                                                                                                                                      1. Independent t test
                                                                                                                                                                                                                                                                                        1. U = Mann-whitney U, z = Z, p = Asymp. sig.
                                                                                                                                                                                                                                                                                      2. 3 + conditions
                                                                                                                                                                                                                                                                                        1. Kruskal-Wallis
                                                                                                                                                                                                                                                                                          1. Independent ANOVA
                                                                                                                                                                                                                                                                                            1. H (df) = Chi-squared value, p = Asymp. sig.
                                                                                                                                                                                                                                                                                        2. Repeated
                                                                                                                                                                                                                                                                                          1. 2 conditions
                                                                                                                                                                                                                                                                                            1. Wilcoxon-Signed-Rank
                                                                                                                                                                                                                                                                                              1. Repeated t test
                                                                                                                                                                                                                                                                                                1. T = (smallest value under "Ranks" table - "mean rank" column), p = asymp. sig.
                                                                                                                                                                                                                                                                                              2. 3 + conditons
                                                                                                                                                                                                                                                                                                1. Friedman's
                                                                                                                                                                                                                                                                                                  1. Repeated ANOVA
                                                                                                                                                                                                                                                                                                    1. X2 (df) = chi-squared value, p= asymp. sig.
                                                                                                                                                                                                                                                                                                2. Testing assumptions
                                                                                                                                                                                                                                                                                                  1. interval/ ratio data
                                                                                                                                                                                                                                                                                                    1. normal distribution
                                                                                                                                                                                                                                                                                                      1. histogram
                                                                                                                                                                                                                                                                                                        1. skewness
                                                                                                                                                                                                                                                                                                        2. normality tests
                                                                                                                                                                                                                                                                                                          1. SPSS output
                                                                                                                                                                                                                                                                                                            1. "tests of normality" - under this will be the name of test to report
                                                                                                                                                                                                                                                                                                              1. D (df) = statistic, p = sig.
                                                                                                                                                                                                                                                                                                                1. if S (p < .050) = BAD (significantly different from a normal dist.
                                                                                                                                                                                                                                                                                                                  1. NS = GOOD
                                                                                                                                                                                                                                                                                                          2. Kolmogorov-Smirnov: D(df) = statistic, p = sig.
                                                                                                                                                                                                                                                                                                          3. homogeneity of variance
                                                                                                                                                                                                                                                                                                            1. LEVENE'S (F ratio)
                                                                                                                                                                                                                                                                                                      2. Questionnaire design
                                                                                                                                                                                                                                                                                                        1. reliability - consistency
                                                                                                                                                                                                                                                                                                          1. internal consistency of each item (esp. if in subscale): consistent scores
                                                                                                                                                                                                                                                                                                          2. validity - is the measure measuring what it claims to?
                                                                                                                                                                                                                                                                                                            1. be specific (eg. rather than "regualrly", use "weekly, daily" etc
                                                                                                                                                                                                                                                                                                              1. no double negatives / double barrelled Q's (eg. no two issues in one Q)
                                                                                                                                                                                                                                                                                                                1. give option of not responding to any sensitive Q's
                                                                                                                                                                                                                                                                                                                  1. Consistent response options! (eg. strongly agree, agree...)
                                                                                                                                                                                                                                                                                                                2. Open Q's
                                                                                                                                                                                                                                                                                                                  1. advantages
                                                                                                                                                                                                                                                                                                                    1. unrestricted response
                                                                                                                                                                                                                                                                                                                      1. detail and additional info- qualitative data
                                                                                                                                                                                                                                                                                                                      2. disadvantages
                                                                                                                                                                                                                                                                                                                        1. difficult to analyse + summarise responses
                                                                                                                                                                                                                                                                                                                          1. time consuming for respondent -> participant effects ?
                                                                                                                                                                                                                                                                                                                          2. Thematic analysis
                                                                                                                                                                                                                                                                                                                            1. identify main themes that emerge from data
                                                                                                                                                                                                                                                                                                                              1. validity: do the themes reflect what the p's said/ meant
                                                                                                                                                                                                                                                                                                                                1. inter-rater reliability in analysing data / extracting themes
                                                                                                                                                                                                                                                                                                                                  1. reflexivity: awareness that researcher can never be unbiased
                                                                                                                                                                                                                                                                                                                                2. Interpretative phenomenological analysis (IPA)
                                                                                                                                                                                                                                                                                                                                  1. most appropriate for finding answers about the experiences of certain groups
                                                                                                                                                                                                                                                                                                                                    1. sampling methods
                                                                                                                                                                                                                                                                                                                                      1. purposive sampling: homogenous p's
                                                                                                                                                                                                                                                                                                                                        1. idiographic approach: individual cases
                                                                                                                                                                                                                                                                                                                                          1. double hermeneutic: p makes sense of experience; researcher understands + interprets
                                                                                                                                                                                                                                                                                                                                        2. phenomenology: the phemomena that we see in the world around us
                                                                                                                                                                                                                                                                                                                                          1. what the researcher brings to the text is important for analysis; engages with p's account of phen. rather than phen. itself
                                                                                                                                                                                                                                                                                                                                            1. analysisng p's account of depression rather than depression as a condition
                                                                                                                                                                                                                                                                                                                                          2. GOAL : generate list of master themes (inclu. p's shared experience and essence of phen.)
                                                                                                                                                                                                                                                                                                                                          3. most appropriate for finding themes in population
                                                                                                                                                                                                                                                                                                                                          4. Content anaysis
                                                                                                                                                                                                                                                                                                                                            1. derives semantic themes from TA and looks at their occurrence
                                                                                                                                                                                                                                                                                                                                          5. Closed Q's
                                                                                                                                                                                                                                                                                                                                            1. advantages
                                                                                                                                                                                                                                                                                                                                              1. quick and easy to analsye / code
                                                                                                                                                                                                                                                                                                                                              2. disadvantages
                                                                                                                                                                                                                                                                                                                                                1. fixed choice of responses
                                                                                                                                                                                                                                                                                                                                                  1. inter-rater reliabilty and bias in coding
                                                                                                                                                                                                                                                                                                                                                  2. closed responses
                                                                                                                                                                                                                                                                                                                                                    1. categorical (male / female)
                                                                                                                                                                                                                                                                                                                                                      1. likert scale
                                                                                                                                                                                                                                                                                                                                                        1. ranking items in order
                                                                                                                                                                                                                                                                                                                                                          1. possibility of acquiescence bias (always agreeing w items)
                                                                                                                                                                                                                                                                                                                                                      2. Interviews and focus groups
                                                                                                                                                                                                                                                                                                                                                        1. identify key themes and terms
                                                                                                                                                                                                                                                                                                                                                          1. Unstructured
                                                                                                                                                                                                                                                                                                                                                            1. no set questions
                                                                                                                                                                                                                                                                                                                                                            2. Semi-structured
                                                                                                                                                                                                                                                                                                                                                              1. Q's set as a GUIDE
                                                                                                                                                                                                                                                                                                                                                              2. Focus group - group interview; interaction between p's is a source of data
                                                                                                                                                                                                                                                                                                                                                                1. similar structure to semi-structured interviews
                                                                                                                                                                                                                                                                                                                                                                  1. less artificial than one on one interview
                                                                                                                                                                                                                                                                                                                                                                    1. less appropriate for sensitive topics
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