On Sun, 7 Dec 2003, Alexander Sirotkin [at Yahoo] wrote: > 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 ?
If that is your question *both* are incorrect. The correct function to use is drop1() (or equivalently Anova from car with the right options). For a detailed comparison of two t tests and the F test (for a term fitted last) see Largey & Spencer (1996) _The Statistician_ 45, 105-9. Once again, aov() and its methods are designed for classical AoV problems which are balanced and in which sequential anova (as implemented here, that is with a common denominator) is appropriate and interpreting coefficients (as in summary.lm) is not. > --- 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 > > -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
