



Dear Help-list, I have a dataframe containing 6 variables, 4 of which are factors, 2 numeric.  I want to create another factor variable (SitePos) by combining 2 existing factors (Site and Position).  I have tried a number of approaches based on trolling the R FAQs, various R webpages, etc., none of which work.  One approach e.g. Data1$SitePos <- paste(Data1$Site, Data1$Position) creates the appropriate "SitePos" values e.g. "CR core" but as character values not as a factor.  A linear model run on the updated dataframe works but notes that it coerces "SitePos" from character to factor e.g. Model.G = lmer(log10(SrCa) ~ SitePos + (1 | Eel), data = Data1) .  The next step of a multiple comparison test on the output of the linear model: Model.G.mct = glht(Model.G, linfct = mcp(SitePos = "Tukey")) fails because the mct does not recognize "SitePos" as a factor and gives error message: "Error in mcp2matrix (model, linfct = linfct): Variable(s) 'SitePos' of class 'character' is/are not contained as a factor in 'model'.  My final step is outputting the mct results:  summary (Model.G.mct, test = adjusted(type = "single-step")).  Any suggestions as to how to create a composite factor variable in the dataframe that would permit execution of the analysis code would be much appreciated.  I am using R version 2.13.0 with packages lme4 and multcomp loaded.  Regards,B Jessop
 		 	   		  
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