Bivariate Correlational Designs: Key Concepts and Validity

What is the primary goal of bivariate correlational designs?

To predict behavior and make association claims.

What type of variables are involved in bivariate correlational designs?

Two measured variables with no manipulation.

What are the two types of associations in bivariate correlational designs?

Positive and Negative associations.

What language signals association claims?

Phrases like 'is linked to', 'is related to', 'is associated with', and 'People who ___ have ___'.

What should be avoided in language when discussing bivariate correlations?

Causal language.

What are predictor variables in bivariate correlational designs?

Variables like meaningful conversations, how couples met, selfishness, and having a dog.

What are outcome variables in bivariate correlational designs?

Variables like happiness, marital satisfaction, number of children, income, and attractiveness.

What is construct validity?

It assesses whether the predictor and outcome variables are measured well.

What is external validity?

It determines if findings generalize to other samples.

What are moderators in the context of bivariate correlations?

Variables that change the strength or direction of an association.

What are the key questions for assessing statistical validity?

Strength of relationship, precision of estimate, replication, and influencing factors.

What does a 95% confidence interval (CI) indicate?

If the CI does not contain 0, the result is significant.

What is the relationship between sample size and confidence interval?

A larger sample leads to a narrower CI and more precision.

What statistical test is used for a continuous predictor and continuous outcome?

Correlation, represented by a scatterplot.

What statistical test is used for a categorical predictor and continuous outcome?

t-test for 2 groups or one-way ANOVA for 3 or more groups.

What are some factors that impact correlations?

Outliers, sample size, curvilinearity, restriction of range, reliability, and shared method variance.

What does statistical significance indicate?

It is significant if p < .05 and the 95% CI does not include 0.

What is power in the context of statistical analysis?

The ability to detect a real effect, increased by larger effect sizes and sample sizes.

Why can correlational studies not establish causation?

They cannot rule out other explanations.

What are the three criteria for establishing causality?

Covariance, temporal precedence, and internal validity.

What is the directionality problem in correlational studies?

It is the uncertainty about which variable came first.

What is the third variable problem?

It refers to an alternative explanation or confound affecting the correlation.

In the example of deep talks and well-being, what is the covariance?

Yes, there is a covariance.

In the example of deep talks and well-being, is there temporal order?

No, they were measured at the same time.

In the example of deep talks and well-being, are there third variables?

Yes, such as a stress-free life.