Thanks a lot to everybody. Two more questions, if you don't mind : How anova() treats non-categorical variables, such as severity in my case ? I was under impression that ANOVA is defined for categorical variables only.
I read about drop1() and I understand that it performs F-test for nested models, correct me if I'm wrong. It is unclear to me, however, how it manages to do this F-test for interactions ? Thanks a lot. --- Peter Dalgaard <[EMAIL PROTECTED]> wrote: > "Alexander Sirotkin [at Yahoo]" > <[EMAIL PROTECTED]> writes: > > > John, > > > > What you are saying is that any conclusion I can > make > > from summary.aov (for instance, to answer a > question > > if physician is a significant variable) will not > be > > correct ? > > Summary.aov is for summarizing aov objects, so > you're lucky to get > something that is sensible at all. You should use > anova() to get > analysis of variance tables. These are sequential so > that you can use > them (give or take some quibbles about the residual > variance) for > reducing the model from the "bottom up". I.e. if you > place "physician" > last, you get the F test for whether that variable > is significant. > However, a more convenient way of getting that > result is to use > drop1(). Even then there's no simple relation to the > two > t-tests, except that the F test tests the hypothesis > that *both* > coefficients are zero, where the t-tests do so > individually. > > > > --- John Fox <[EMAIL PROTECTED]> wrote: > > > Dear Spencer and Alexander, > > > > > > In this case, physician is apparently a factor > with > > > three levels, so > > > summary.aov() gives you a sequential ANOVA, > > > equivalent to what you'd get > > > from anova(). There no simple relationship > between > > > the F-statistic for > > > physician, which has 2 df in the numerator, and > the > > > two t's. (By the way, I > > > doubt whether a sequential ANOVA is what's > wanted > > > here.) > > > > > > Regards, > > > John > > > > > > At 09:17 AM 12/6/2003 -0800, Spencer Graves > wrote: > > > > The square of a Student's t with "df" > degrees > > > of freedom is an F > > > > distribution with 1 and "df" degrees of > freedom. > > > > hope this helps. spencer graves > > > > > > > >Alexander Sirotkin [at Yahoo] wrote: > > > > > > > >>I have a simple linear model (fitted with > lm()) > > > with 2 > > > >>independant > > > >>variables : one categorical and one integer. > > > >> > > > >>When I run summary.lm() on this model, I get a > > > >>standard linear > > > >>regression summary (in which one categorical > > > variable > > > >>has to be > > > >>converted into many indicator variables) which > > > looks > > > >>like : > > > >> > > > >> Estimate Std. Error t value > Pr(>|t|) > > > >>(Intercept) -3595.3 2767.1 -1.299 > 0.2005 > > > >>physicianB 802.0 2289.5 0.350 > 0.7277 > > > >>physicianC 4906.8 2419.8 2.028 > 0.0485 * > > > >>severity 7554.4 906.3 8.336 > 1.12e-10 > > > *** > > > >> > > > >>and when I run summary.aov() I get similar > ANOVA > > > table > > > >>: > > > >> Df Sum Sq Mean Sq F value > > > Pr(>F) > > > >>physician 2 294559803 147279901 3.3557 > > > 0.04381 > > > >>* > > > >>severity 1 3049694210 3049694210 69.4864 > > > 1.124e-10 > > > >>*** > > > >>Residuals 45 1975007569 43889057 > > > >> > > > >>What is absolutely unclear to me is how > F-value > > > and > > > >>Pr(>F) for the > > > >>categorical "physician" variable of the > > > summary.aov() > > > >>is calculated > > > >>from the t-value of the summary.lm() table. > > > >> > > > >>I looked at the summary.aov() source code but > > > still > > > >>could not figure > > > >>it. > > > >> > > > >>Thanks a lot. > > > >> > > > >>__________________________________ > > > >> > > > > > >> > > > >>______________________________________________ > > > >>[EMAIL PROTECTED] mailing list > > > > > > >>https://www.stat.math.ethz.ch/mailman/listinfo/r-help > > > >> > > > > > > > >______________________________________________ > > > >[EMAIL PROTECTED] mailing list > > > > > > >https://www.stat.math.ethz.ch/mailman/listinfo/r-help > > > > > > > > > ----------------------------------------------------- > > > John Fox > > > Department of Sociology > > > McMaster University > > > Hamilton, Ontario, Canada L8S 4M4 > > > email: [EMAIL PROTECTED] > > > phone: 905-525-9140x23604 > > > web: www.socsci.mcmaster.ca/jfox > > > > > > ----------------------------------------------------- > > > > > > > ______________________________________________ > > [EMAIL PROTECTED] mailing list > > > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > > > > -- > O__ ---- Peter Dalgaard Blegdamsvej > 3 > c/ /'_ --- Dept. of Biostatistics 2200 Cph. N > > (*) \(*) -- University of Copenhagen Denmark > Ph: (+45) 35327918 > ~~~~~~~~~~ - ([EMAIL PROTECTED]) > FAX: (+45) 35327907 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help