Question

Reviewing the Three Causal Criteria

1. Why can’t a simple bivariate correlational study meet all three criteria for establishing causation?

Establishing Temporal Precedence with Longitudinal Designs

1. Why is a longitudinal design considered a multivariate design?

2. What are the three kinds of correlations obtained from a longitudinal design? What does each correlation represent?

3. Describe which patterns of temporal precedence are indicated by different cross-lag correlational results.

Ruling Out Third Variables with Multiple-Regression Analyses

1. Describe what it means to say that some variable “was controlled for” in a multivariate study.

2. How many criterion variables are there in a multiple-regression analysis? How many predictor variables?

3. What does a significant beta mean? What does a nonsignificant beta mean?

4. Give at least two phrases indicating that a study used a multiple-regression analysis.

5. What are two reasons that multiple-regression analyses cannot completely establish causation?

Getting at Causality with Pattern and Parsimony

1. Why do many researchers find pattern and parsimony an effective way to support a causal claim?

2. What is a responsible way for journalists to cover single studies on a specific topic?

Mediation

1. Explain why each of the five steps examining a mediation hypothesis is important to establishing evidence for a mediator.

2. Think of a possible mediator for the relationship between exposure to sex on TV and chance of pregnancy. Sketch a diagram of the mediator you propose, following Figure 9.11. (It is ok to just describe your sketch)

Multivariate Designs and the Four Validities

1. Give an example of a question you would ask to interrogate each of the four

validities for a multivariate study.

Answer 1

Establishing Temporal Precedence with Longitudinal Designs

Why can't a straightforward bivariate correlational study meet all 3 criteria for establishing causation? (1) Covariance: affirmative, tried that there's a comelation! (2) Temporal Precedence: cannot say that variable came 1st and caused the second variable (3) Internal Validity: third variables aren't sometimes controlled for! Longitudinal style: Can offer proof for Temporal Precedence by measurement the identical variable within the same individuals at totally different points in time. This could check causative claims Cross-Sectional Coirelations: Test to determine whether or not 2 variables measured at the identical purpose in time are Autoorre lations: Evaluat ing the association/correlation of every variable with itself over time referred to as autocorrelations as a result of the verify the correlation of 1 variable with itself, measured on 2 totally different occasions Cross-Lag Correlations Shows whether or not the sooner live of 1 variable is related to the later measure of the opposite variable, this therefore addresses the radial asymmetry downside and helps establish Temporal Precedence!! By seeing the cross-lag correlation, we are able to see however individuals amendment over time (temporal precedence)!

Why can't a straightforward bivariate correlational study meet all 3 criteria for establishing causation? (1) Covariance: affirmative, tried that there's a comelation! (2) Temporal Precedence: cannot say that variable came 1st and caused the second variable (3) Internal Validity: third variables aren't sometimes controlled for! Longitudinal style: Can offer proof for Temporal Precedence by measurement the identical variable within the same individuals at totally different points in time. This could check causative claims Cross-Sectional Coirelations: Test to determine whether or not 2 variables measured at the identical purpose in time are Autoorre lations: Evaluat ing the association/correlation of every variable with itself over time referred to as autocorrelations as a result of the verify the correlation of 1 variable with itself, measured on 2 totally different occasions Cross-Lag Correlations Shows whether or not the sooner live of 1 variable is related to the later measure of the opposite variable, this therefore addresses the radial asymmetry downside and helps establish Temporal Precedence!! By seeing the cross-lag correlation, we are able to see however individuals amendment over time (temporal precedence)!

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