Dear Matthew, First of all I'm forwarding this to R-SIG-Mixed, which is a more appropriate list for your question. Using a mixed effect with only 5 levels is a borderline situation. Douglas Bates recommends at least 6 levels in order to get a more or less reliable estimate. So I would consider the populations as fixed effects. Do you have repeated measurements of individuals within your populations? If you do you could use those as random effects.
Your anova tests whether the variances of the random slope on SPI is zero. I think you might want this: mod1 <- lm(height ~ SPI * population + covariate1 + covariate2) mod2 <- lm(height ~ SPI + population + covariate1 + covariate2) anova(mod1, mod2) HTH, Thierry ------------------------------------------------------------------------ ---- ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodology and quality assurance Gaverstraat 4 9500 Geraardsbergen Belgium tel. + 32 54/436 185 [EMAIL PROTECTED] www.inbo.be To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey -----Oorspronkelijk bericht----- Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Namens Matthew Keller Verzonden: dinsdag 9 september 2008 1:10 Aan: R Help Onderwerp: [R] correct lme syntax for this problem? Hello all, I am about to send off a manuscript and, although I am fairly confident I have used the lme function correctly, I want to be 100% sure. Could some kind soul out there put my mind at ease? I am simply interested in whether a predictor (SPI) is related to height. However, there are five different populations, and each may differ in mean level of height as well as the relationship between SPI and height. Thus, I also want to a) account for mean level differences in height and b) check whether the relationship between height and SPI is different between the groups. I hope this is sufficient information. height, SPI, covariate1, and covariate2 are numeric. population is a factor with 5 levels. Here are the steps I took: summary(mod1 <- lme(height ~ SPI + covariate1 + covariate2, random = ~ SPI | population)) summary(mod2 <- lme(height ~ SPI + covariate1 + covariate2, random = ~ 1 | population)) anova(mod1,mod2) #this checks whether there is evidence for IQ & SPI being related differently between the 5 populations. Is this correct? THANKS! Matt -- Matthew C Keller Asst. Professor of Psychology University of Colorado at Boulder www.matthewckeller.com ______________________________________________ R-help@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. Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is door een geldig ondertekend document. The views expressed in this message and any annex are purely those of the writer and may not be regarded as stating an official position of INBO, as long as the message is not confirmed by a duly signed document. ______________________________________________ R-help@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.
