Psychology 202a Advanced Psychological Statistics November 10, 2015.

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Presentation transcript:

Psychology 202a Advanced Psychological Statistics November 10, 2015

Introducing multiple linear regression Multiple regression has more than one predictor on the right hand side of the equation. Example:

When is multiple regression like simple regression? Illustration with artificial data (digression in SAS) The simple regression slope is identical to the multiple regression slope only when the predictors are perfectly uncorrelated. That won’t happen except by design. Here’s why:

Added variable plots In order to find what is unique about the relationship between a particular predictor (X 1 ) and Y –Isolate the part of Y that cannot be described by other predictors –Isolate the part of X 1 that cannot be described by other predictors –Examine the relationship

Added variable plots (cont.) What part of Neuroticism cannot be predicted by Depression? The residuals from the regression of Neuroticism on Depression. What part of Agreeability cannot be predicted by Depression? The residuals from the regression of Agreeability on Depression.

Added variable plots (cont.) The added variable plot looks at the relationship between those two sets of residuals. So does multiple regression. Illustration in SAS Doing AV plots in R

Interpretation of multiple regression Multiple regression, just like simple regression, is a model for the conditional mean. A slope in multiple regression represents change in conditional mean associated with a one-unit change in the predictor… …while holding constant the other predictors.

Interpretation of multiple regression The added variable plot gives us a way of understanding what it means to “hold constant” some variables. In multiple regression, we look at the predictive ability of each independent variable… …after quite literally removing the effects of the other variables.