From: Kevin J Emerson <kemerson_at_uoregon.edu>

Date: Mon 17 Jul 2006 - 12:18:10 EST

}

Kevin Emerson

Center for Ecology and Evolutionary Biology 1210 University of Oregon

Eugene, OR 97403

**USA
**

kemerson@uoregon.edu

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Mon Jul 17 12:24:58 2006

Date: Mon 17 Jul 2006 - 12:18:10 EST

# qtl is the original data.frame, and my dependent var in this case is # qtl$CPP.

for (j in (i+1):41) { marker1 <- rbind(marker1,names(qtl)[i]) marker2 <- rbind(marker2,names(qtl)[j]) tmp2 <- summary(aov(tmp$CPP ~ tmp[,i] * tmp[,j]))[[1]] p.interaction <- rbind(p.interaction, tmp2$"Pr(>F)"[3]) }

}

I have two questions:

(1) is there a nicer way to do this without having to invoke for loops?

(2) my other dependent variables are categorical in nature. I need

basically the same information - I am looking for information regarding the
interaction of predictors on a categorical variable. Any ideas on what
tests to use? (I am new to analysis of all-categorical data).

Kevin Emerson

Center for Ecology and Evolutionary Biology 1210 University of Oregon

Eugene, OR 97403

kemerson@uoregon.edu

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Mon Jul 17 12:24:58 2006

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