Dear R-group, Could somebody recommend a package that can deal with a multinomial response variable (choice of breeding tactic in mice, which has four unordered levels), multiply-imputed data (generated using the Amelia package) and two non-nested random effects: individual identity (133 individuals made up to four choices each) and year (for which there are six levels and sample size varies between years)?
I've tried sabreR, drm, mixcat and mlogit but none of them seem able to accommodate multiply-imputed datasets. The most promising package Ive found so far is Zelig, which can handle multiply-imputed data and either multinomial responses OR random effects (but seemingly not both). I could randomly select one case per individual and run the following model (with year as a fixed rather than random effect): z.out <- zelig(as.factor(tactic) ~ mass+age+year, model = "mlogit", data = a.out$imputations) but it probably isn't the most elegant solution. Does anybody have any suggestions? Thanks in advance, Davina ------------------------------------------ Animal, Plant and Environmental Sciences University of the Witwatersrand South Africa <html><p><font face = "verdana" size = "0.8" color = "navy">This communication is intended for the addressee only. It is confidential. If you have received this communication in error, please notify us immediately and destroy the original message. You may not copy or disseminate this communication without the permission of the University. Only authorized signatories are competent to enter into agreements on behalf of the University and recipients are thus advised that the content of this message may not be legally binding on the University and may contain the personal views and opinions of the author, which are not necessarily the views and opinions of The University of the Witwatersrand, Johannesburg. All agreements between the University and outsiders are subject to South African Law unless the University agrees in writing to the contrary.</font></p></html> [[alternative HTML version deleted]]
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