Dear Bernd, dear list, Bernd Weiss a écrit : [ ... ]
> Have a look at "MiMa" at Wolfgang Viechtbauer's page. Is that what > you are looking for? > > <http://www.wvbauer.com/downloads.html> As far as I can tell, mima does what I mean to do, but there are some limits : - mima works on effects, and therefore has an "unusual" form in R models - as far as I can tell, mima allows to asses the effect of variables *nesting* studies, but not of variables *crossed* in each study ; therefore, ypou cannot directly test the effect of such variables ; - as far as I can tell, the variables of interest ("moderators", in mima parlance) can be either two-level factors, booleans or numeric variables, i. e variables having a single regression coeffiient : mima builds an estimator for the regression coefficient of each variable and its variance, and tests by a Z-test. This is not applicable to n-valued factors (n>2) or ordered factors, which could be tested by {variance|deviance} analysis. Of those limitations, the least important is the first. The second may be worked around (at least for cases I have in mind writing this), but the last one is quite serious. A cursory look at mima code lets me think that it may be used to implement a form of deviance analysis ; in this case, the recoding of n-valued factors is something standard in R, that can be easily retrofitted. In short : mima will be quite helpful, but is not really what I had in mind. to be more precise, what I want to do is : mod1<-foo(Outcome~Treatment*(Presentation+Design), random=(1|Study %in% Design), sd=Sds, data=RawData, ...) Testing for an interaction of Treatment and Presentation (i. e. Is the efficacy of the treatment the same for all possible clinical presentations ?) would be done with mod2<- update(mod1,.~.-Treatment:Presentation) # build a restricted #model, nested in the first anova(mod1,mod2) # test it with some form of deviance analysis Similarly, testing for possible bias of design would be done with mod3<- update(mod1,.~.-Treatment:Design) anova(mod1,mod3) Currently, mima seems to allow for this latter comparison (by building and testing a regression coefficient for Design), but not the former. Sincerely, Emmanuel Charpentier ______________________________________________ [email protected] 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.
