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Is there a difference between ANCOVA (as performed under the 'General Linear Model (GLM)') and Hierarchical Regression (as performed under 'Regression') in SPSS?

I am testing the main effects and interaction of X1 (continuous) and X2 (categorical) on Y (continuous).

I understand GLM incorporates regression and one of the main advantages of using GLM over the regression function is that GLM (factor) creates dummy coding. In regression, this must be done prior to inputting the categorical factor in the analysis box. The same also applies to the interaction product.

I personally find GLM (ANCOVA) output easier to understand.

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What do you mean under "hierarchical regression"? And please provide the two commands in syntax which you are comparing. –  ttnphns Jan 17 '12 at 12:33
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up vote 5 down vote accepted

There really isn't a difference. In matrix algebra form, regression, ANOVA and ANCOVA are all written as

$Y = X\beta + \epsilon$

They arose in different fields and the output is typically formatted differently, but the meaning is the same. However, in the usual usage of the words, regression incorporates the other two, because ANOVA is usually used only when all the independent variables are categorical; ANCOVA when one is continuous (usually) and the others categorical, and regression for any IVs at all.

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