Ex Post Facto and Correlational Research

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Chapter 12
Amber Hines
Flashcards by Amber Hines, updated more than 1 year ago
Amber Hines
Created by Amber Hines almost 7 years ago
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*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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