# lm ANOVA vs. AOV

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## lm ANOVA vs. AOV

 Why would someone use lm and ANOVA (anova(lm(x))) instead of AOV (or   the other way around)? The mean squares and sum of squares are the same, but the F values   and p-values are slightly different. I am modeling a dependent~independent1*independent2. Thanks, Matt Bridgman         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: lm ANOVA vs. AOV

 The underlying least squares arithmetic of aov and lm is identical. In R, the QR algorithm is used.  The difference between the two is intent of the analysis and the default presentation of the results. With lm [Linear Model], the focus is on the effect of the individual columns of the predictor matrix.  The columns are usually interpreted as values of real-valued observations.  The regression coefficients are usually meaningful and interesting. With aov [Analysis Of Variance], the focus is on the effects of factors.  These are multi-degree of freedom effects associated with categorical variables.  The arithmetic is based on a set of dummy variables constructed from a contrast matrix.  The individual regression coefficients themselves are not easily interpretable. You can pursue the details of this summary in any good statistical methods book. Rich ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.