I have the following results for an ANOVA comparing two nested models. I wasn't sure how I am supposed to report this result in the area of psychology. Specifically, am I supposed to report the DF's or just the F ratio? I could manually calculate the degrees of freedoms, but there must be a reason why R does not give this information, i.e. those are not conventionally used in the reporting? Any pointers would be greatly appreciated.> anova(fit1, fit2)Analysis of Variance Table Model 1: fit1 Model 2: fit2 Res.Df RSS Df Sum of Sq F Pr(>F) 1 373 19.908 2 374 30.717 -1 -10.809 202.53 < 2.2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 [[alternative HTML version deleted]]
fit1, the unrestricted model, includes 1 more regressor than fit2, the restricted model. Testing the models against each other means that fit2 is "equal to" fit1, assuming that the coefficient on the additional regressor that is included in fit1 is restricted to zero. Your F-test is thus whether this one extra regressor is significantly different from zero, and the F-test is therefore on 1 and n-k degrees of freedom, where 1 is the number of restrictions, n is the number of observations and k is the number of coefficients in the unrestricted model. So unless you do something a little more "spectacular" than just adding one regressor and checking its significance, this is understood I would say. That said, I am not a psychologist. HTH, Daniel zugi young wrote:> > I have the following results for an ANOVA comparing two nested models. I > wasn't sure how I am supposed to report this result in the area of > psychology. Specifically, am I supposed to report the DF's or just the F > ratio? I could manually calculate the degrees of freedoms, but there must > be > a reason why R does not give this information, i.e. those are not > conventionally used in the reporting? > > Any pointers would be greatly appreciated. > >> anova(fit1, fit2) > Analysis of Variance Table > > Model 1: fit1 > Model 2: fit2 > Res.Df RSS Df Sum of Sq F Pr(>F) > 1 373 19.908 > 2 374 30.717 -1 -10.809 202.53 < 2.2e-16 *** > --- > Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 > > [[alternative HTML version deleted]] > > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >-- View this message in context: http://r.789695.n4.nabble.com/reporting-ANOVA-for-nested-models-tp3796957p3797302.html Sent from the R help mailing list archive at Nabble.com.
On Sep 7, 2011, at 20:57 , zugi young wrote:> I have the following results for an ANOVA comparing two nested models. I > wasn't sure how I am supposed to report this result in the area of > psychology. Specifically, am I supposed to report the DF's or just the F > ratio? I could manually calculate the degrees of freedoms, but there must be > a reason why R does not give this information, i.e. those are not > conventionally used in the reporting? > > Any pointers would be greatly appreciated.What do you mean by "compute" degrees of freedom? It would seem rather clear from the output that the F test is on (1, 373) d.f. (the denominator d.f. is taken from the largest of the two models). As for what to reporting the d.f., some journals do like to see them, mostly to allow the reader to sanity-check the results. In models which contain variance components (or should have contained them), the denominator d.f. can be revealing. As can they if you committed everyone's favorite blunder, category codes used as quantitative variables.>> anova(fit1, fit2) > Analysis of Variance Table > > Model 1: fit1 > Model 2: fit2 > Res.Df RSS Df Sum of Sq F Pr(>F) > 1 373 19.908 > 2 374 30.717 -1 -10.809 202.53 < 2.2e-16 *** > --- > Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.-- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com "D?den skal tape!" --- Nordahl Grieg