Control for all variables when predicting for a continuous outcome
Simultaneous regression is the same as multiple regression. All variables are entered into the model at the same time with simultaneous regression. The beta coefficients and change in R-squared are interpreted, given that the statistical assumptions of normality, linearity, and homoscedasticity for the model are met. In simultaneous regression, each predictor variable controls for all other variables in the interpretation of R-squared and beta coefficients. Click on the Multiple Regression button below to learn how to conduct simultaneous regression in SPSS.
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