Podcast
Questions and Answers
In a(n) ____, two variables measured at the same time are associated.
In a(n) ____, two variables measured at the same time are associated.
cross sectional correlation
If an earlier measure of a variable is associated with a later measure of the same variable, a(n) ____ occurs.
If an earlier measure of a variable is associated with a later measure of the same variable, a(n) ____ occurs.
autocorrelation
In a(n) ____, an earlier measure of one variable is associated with a later measure of a different variable.
In a(n) ____, an earlier measure of one variable is associated with a later measure of a different variable.
cross lag correlation
These three types of correlations are usually found in ____ designs.
These three types of correlations are usually found in ____ designs.
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A(n) ____ is conducted over a longer period of time than a typical correlational study to help establish ____.
A(n) ____ is conducted over a longer period of time than a typical correlational study to help establish ____.
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A(n) ____ considers more than two variables in the same analysis and can help improve ____.
A(n) ____ considers more than two variables in the same analysis and can help improve ____.
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A ____ is a variable that explains how the two main variables are related in different ways depending on the situation.
A ____ is a variable that explains how the two main variables are related in different ways depending on the situation.
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A ____ explains why two variables may be related based on an internal factor that connects them.
A ____ explains why two variables may be related based on an internal factor that connects them.
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Multiple regression can help eliminate problems with ____ by controlling for potential third variables.
Multiple regression can help eliminate problems with ____ by controlling for potential third variables.
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It sets ____ variable(s) that influence the ____ variable, which is the outcome of interest.
It sets ____ variable(s) that influence the ____ variable, which is the outcome of interest.
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Effect sizes in multiple-regression analyses can be represented by both ____, which is a standardized effect size, and ____, which is an unstandardized effect size.
Effect sizes in multiple-regression analyses can be represented by both ____, which is a standardized effect size, and ____, which is an unstandardized effect size.
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What is a parsimonious explanation?
What is a parsimonious explanation?
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What is the best interpretation of β = −0.39 for foreign-language anxiety?
What is the best interpretation of β = −0.39 for foreign-language anxiety?
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What does the beta for foreign-language anxiety mean?
What does the beta for foreign-language anxiety mean?
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Does Sammy want to find out whether parenting style explains the association between self-esteem and behavior problems?
Does Sammy want to find out whether parenting style explains the association between self-esteem and behavior problems?
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Does Sammy want to find out whether self-esteem in elementary school predicts behavior problems in middle school?
Does Sammy want to find out whether self-esteem in elementary school predicts behavior problems in middle school?
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Does Sammy want to find out whether there is an association between self-esteem and behavior problems even after adjusting for experience with bullying?
Does Sammy want to find out whether there is an association between self-esteem and behavior problems even after adjusting for experience with bullying?
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Does Sammy want to find out whether self-esteem and behavior problems have a mutually reinforcing relationship?
Does Sammy want to find out whether self-esteem and behavior problems have a mutually reinforcing relationship?
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The largest beta in a multiple-regression analysis is the predictor that has the strongest relationship with the criterion variable.
The largest beta in a multiple-regression analysis is the predictor that has the strongest relationship with the criterion variable.
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A multiple-regression analysis can control for more than one variable at a time.
A multiple-regression analysis can control for more than one variable at a time.
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Multiple regression establishes temporal precedence as long as it controls for potential third-variable problems.
Multiple regression establishes temporal precedence as long as it controls for potential third-variable problems.
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A multiple-regression analysis that accounts for third variables can establish causality.
A multiple-regression analysis that accounts for third variables can establish causality.
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Study Notes
Correlational Designs
- Cross-sectional correlation: Involves measuring two variables at the same time to identify associations.
- Autocorrelation: Measures the association between an earlier and a later measure of the same variable.
- Cross-lag correlation: Examines the association between an earlier measure of one variable and a later measure of a different variable.
- These three correlations are typically found in longitudinal designs.
Study Types
- Longitudinal study: Conducted over an extended period to establish temporal precedence.
- Multiple regression analysis: Considers more than two variables in the analysis to improve internal validity.
Variables in Analysis
- Moderator: A variable that explains how the relationship between two main variables differs based on situational factors.
- Mediator: Explains the internal factors connecting two variables and why they may be related.
Multiple Regression
- Helps to improve internal validity by controlling for potential third variables.
- Sets predictor variables that influence the criterion variable, the outcome of interest.
- Effect sizes can be represented by beta (β), a standardized effect size, and b, an unstandardized effect size.
Parsimonious Explanation
- The simplest explanation for a phenomenon compared to more complex alternatives.
Research Findings
- In a study on foreign-language anxiety, a beta of β = −0.39 indicates that higher anxiety negatively affects foreign-language achievement, significantly more than the effect of academic achievement (β = 0.29).
- The negative beta suggests people with lower anxiety levels perform better in foreign-language achievement when controlling for other variables.
Longitudinal vs. Multiple Regression Scenarios
- Multiple regression is suited for examining how parenting style relates to self-esteem and behavior problems.
- Longitudinal studies predict how self-esteem in elementary school affects behavior problems in middle school.
- Multiple regression assesses the relationship between self-esteem and behavior after adjusting for bullying experiences.
- Longitudinal studies are appropriate for investigating if self-esteem and behavior problems reinforce each other over time.
True or False Statements
- The largest beta indicates the strongest predictor in a multiple regression analysis: True.
- A multiple regression can control for multiple variables simultaneously: True.
- Controlling for third-variable problems in multiple regression establishes temporal precedence: False.
- Multiple regression accounting for third variables can establish causality: False.
Implications of Cognitive Job Study
- A study suggests that cognitively demanding jobs correlate with cognitive benefits later in life, but this relationship may be influenced by educational background, highlighting the role of third variables.
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Description
Dive into the intricacies of correlational designs in psychology with these flashcards. You'll explore the concepts of cross-sectional, autocorrelation, and cross-lag correlations as well as their applications in longitudinal studies. Test your understanding and reinforce key terminology essential for psychology students.
