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Erstellt von Amber Hines
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| Frage | Antworten |
| *Research conducted after variation in the variable of interest has already been determined in the natural course of events. *Used when randomization and manipulation of variable characteristics is not possible. | Ex Post Facto Research (Latin for after the fact) Also sometimes called casual comparative |
| What are the two basic designs of ex post facto research? | *Begin with subjects differing on an independent variable -try to determine consequences *Begin with subjects differing on a dependent variable-try to determine the antecendent (cause) |
| A characteristic that a subject possesses before the study begins | Attribute independent variable |
| Approaches are very similar between these two types of research | Ex Post Facto and Experimental |
| Starts with equivalent groups and exposes them to different treatments | Experimental Research |
| Starts with different groups and tries to determine the consequences or antecendents of the difference | Ex Post Facto Research |
| Mistakenly attributing causation based on a relationship between two variables | Post hoc fallacy |
| To establish a conclusion that X is the cause of Y, you should verify these three things: | *Establish that a statistical relationships exists b/t x and y *Establish that x preceded y in time *Establish that other factors did not determine y |
| A relationship where two variables have no effect on each other, but are related because of a third variable | Spurious Relationship |
| A relationship where a change in one variable can be predicted from a change in the other | Statistical Relationship |
| What are the 5 stages of Ex Post Facto Research? | *State the problem *Select your groups to compare *Choose b/t proactive/retroactive design *Collect data on independent and dependent variables *Analyze and interpret data |
| Type of Ex Post Facto design that begins with subjects grouped on the basis of an independent variable (Ex. father present/father not present) | Proactive ex post facto research |
| Type of Ex Post Facto design that seeks possible antecedent causes for a pre-existing dependent variable | Retroactive ex post facto research |
| What are some alternative explanations in ex post facto research? | *Common Cause *Reverse Causality *Other possible independent variables |
| Strategies used to improve the credibility of ex post facto research provide... | Partial Control |
| What are some of the specific partial control strategies? | *Matching *Homogenous groups *Build extraneous variables into the design *Analysis of covariance *Partial Correlations |
| This partial control strategy is likely to greatly reduce the number of subjects that can actually be used in the final analysis | Matching |
| True or False: Using homogeneous groups reduces external validity of the study | True |
| This partial control strategy adjusts scores on the dependent variable for any initial differences on the extraneous variable | Analysis of Covariance (ANCOVA) |
| 2x4x2 higher-order interaction F test is an example of this type of partial control strategy: | Extraneous Variables |
| Investigates the extent to which variables are related and the direction of the relationship | Correlational Research |
| How does correlational research differ from ex post facto? | *Correlational relates two or more variable measures from the same group of subjects *Ex post facto compares two or more groups on the same variable |
| In correlational research, the sign + or - indicates what? | The direction of the relationship *Height and weight are positively correlated *Temperature and heating bills are negatively correlated |
| What do + 1.00 and - 1.00 represent and why? | *A perfect positive and perfect negative relationship *Size of the correlation and coefficient indicates the strength of the relationship b/t the variables. |
| What are the uses of Correlation? | *Assessing relationships *Assessing consistency *Prediction |
| True or False: Often a correlational study is mainly exploratory | True: Identify patterns of relationships based on theory |
| True or False: Correlations can be used to measure consistency | True: They can be used to measure consistency (or lack of) in a wide variety of cases |
| Reliability (Consistency) of a test can be assessed through: | *Correlating test-retest *equivalent forms *split-half scores |
| True or false: When you find two variables are correlated, you can use one variable to predict the other. | True *Ex. freshman GPA from high school grades and aptitude tests (prediction may not hold for every case) |
| What are the stages to designing a correlational study? | *Specify the relationship by asking a question about the relationship b/t two variables of interest *Determine how the constructs will be quantified *Select the sample to represent the population *Collect the data and calculate the coefficient of correlations |
| Name the 6 correlation coefficients | *Pearson's product moment correlation-r (interval or ratio data) *Spearman's Rho or Rank- (P) (data are ranks rather than raw scores) *Kendall's tau b (ordinal data-square contingency tables) *Kendall's tau c (ordinal data-rectangular contingency tables) *Phi Coefficient - (Nominal variables-2x2 contingency table) *Cramer's V- (Nominal variables-other than a 2x2 table) |
| Look at Measures of Relationships Table- What are the three types? | *Nominal *Ordinal *Interval |
| What are the considerations for interpreting a correlation coefficient? | *Absolute size and predictive value *Correlation as effect size (look at Cohen's stuff) *Assess in relation to other correlations of the same variables *Statistical significance *Practical Utility |
| Does correlation indicate a cause and effect relationship? | No |
| This is used to determine the relationship b/t two variables when the third is removed | Partial Correlation |
| A correlational procedure that examines the relationships among several variables, enables researchers to find the best possible weighting of two or more independent variables to yield a maximum correlation with a single dependent variable. | Multiple Regression |
| A statistical procedure related to multiple regression, but differs in that the criterion is a categorical variable rather than a continuous one | Discriminant analysis |
| Analyzes the intercorrelations among a large set of measures to identify a smaller number of common factors | Factor analysis |
| Adds more than one dependent variable to the prediction equation | Canonical correlations |
| An independent variable that an investigator can directly manipulate | Active Independent Variable |
| This is an alternative explanation in Ex Post Facto research, in which the independent and dependent variable are two separate results of a third variable | Common Cause |
| This is an alternative explanation in Ex Post Facto research, in which the reverse of the suggested hypothesis could also account for the finding | Reverse Causality |
| The assumption that a statistically significant correlation also has practice signficance | Significance Fallacy |
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