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copied!<p>From <code>?glmulti</code>, </p> <blockquote> <p>If [the argument <code>data</code> is] not specified, glmulti will try to find the data in the environment of the formula, from the fitted model passed as y argument, or from the global environment.</p> </blockquote> <p>However, when you specify <code>data = temp1</code>, <code>glmulti</code> apparently looks in the global environment for this object. Therefore, you may need to assign your randomly selected data to the global environment (I've renamed things a little to try and keep names and objects in check):</p> <pre><code>glm.random2<-function(df){ reps=5 output<-matrix(NA, ncol=1, nrow=0) while (length(output[,1])<reps) { ## Here things are different temp2 <- ddply(df,.(study_id),randomRows,1) names(temp2)[2]<-"cOntinent" assign("temp1",temp2,envir=.GlobalEnv) ## Note the slightly modified formula, to check whether ## gmulti looks for terms in temp1 or simply as named objects in the environment ## It looks like the former, which is good. temp3 <- glmulti(yi_pos ~ cOntinent+taxatype+metric, data = temp1, family = gaussian( link = log), crit = aic, plotty = F, report = F) temp4 <- noquote(paste(summary(temp3)$bestmodel[1])) output<-rbind(output,temp4) ## Remove the object temp1 from the global environment rm(temp1,envir=.GlobalEnv) } write.table(output, "output.glm.random1.txt", append=TRUE, sep="\t", quote=FALSE) } # run function - no error for me! glm.random2(df) </code></pre> <p>You might want to check with the package maintainer to see if this is the intended way for <code>glmulti</code> to work.</p>

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