On Jul 16, 2011, at 10:21 AM, B Jessop wrote:
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$Position)
creates the appropriate "SitePos" values e.g. "CR core" but as
character values not as a factor.
In one line you could have written:
Data1$SitePos <- factor( paste(Data1$Site, Data1$Position) )
Or you could have created an interaction:
Data1$SitePos <- interaction(Data1$Site, Data1$Position)
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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David Winsemius, MD
West Hartford, CT
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