Chapter 9: Multivariate Correlational Research

(FINAL EXAM)

Multivariate design

A study designed to test an association involving more than two measured variables. (page 238)

Longitudinal design

A study in which the same variables are measured in the same people at different points in time. (page 239)

Cross-sectional correlation

In a longitudinal design, a correlation between two variables that are measured at the same time. (page 239)

Autocorrelation

In a longitudinal design, the correlation of one variable with itself, measured at two different times. (page 240)

Cross-lag correlation

In a longitudinal design, a correlation between an earlier measure of one variable and a later measure of another variable. (page 241)

Multiple regression

A statistical technique that computes the relationship between a predictor variable and a criterion variable, controlling for other predictor variables. Also called multivariate regression. (page 244)

Control for

Holding a potential third variable at a constant level (statistically or experimentally) while investigating the association between two other variables. See also control variable, multiple regression. (page 245)

Criterion variable

The variable in a multiple-regression analysis that the researchers are most interested in understanding or predicting. Also called dependent variable. (page 247)

Predictor variable

A variable in multiple-regression analysis that is used to explain variance in the criterion variable. Also called independent variable. (page 248)

Parsimony

The degree to which a theory provides the simplest explanation of some phenomenon. In the context of investigating a claim, the simplest explanation of a pattern of data; the best explanation that requires making the fewest exceptions or qualifications. (page 256)

Mediator

A variable that helps explain the relationship between two other variables. Also called mediating variable. (page 259)