PSCH 443 Multiple Regression Partial and Semi Partial Correlation

Multiple Regression

A statistical technique used to model the effects of multiple predictor variables on an outcome variable.

Partial Correlation

A measure of the relationship between two variables while holding a third variable constant.

Semi-Partial Correlation

A measure that indicates the relationship between an X variable and a Y variable while holding the covariation of X with a third variable constant.

Outcome Variable

The variable that is being predicted or explained in a regression analysis, often denoted as Y.

Predictor Variable

The variable(s) that are used to predict or explain the outcome variable, often denoted as X.

Multicollinearity

A situation in regression analysis where predictor variables are highly correlated with each other, which can complicate the interpretation of the model.

Residual Variation

The variation in the outcome variable that cannot be explained by the predictor variables; often referred to as error.

Background Variable

A variable that may influence the relationship between a predictor and the outcome, but is not the focus of the main analysis.

Correlational Research Design

A research design that examines the relationships between variables without manipulating them.

Complex Research Questions

Questions that involve multiple factors affecting an outcome variable, requiring more advanced analysis than simple bivariate relationships.