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 n!
ot 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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