I am running a large mixed model, 65k entries on 11 fixed effects and one random. One of the fixed effects is "Course" a factor that takes on 14 different values >levels(Master.complete$Course) [1] "B101" "B2A" "B2B" "B2C" "C118A" "C118B" "C118C" "C2A" "C2B" [10] "C2C" "N101" "P7A" "P7B" "P7C"
and another "Yfrm7A" that is continuous >summary(Master.complete$Yfrm7A) Min. 1st Qu. Median Mean 3rd Qu. Max. -5.25000 -0.75000 0.00000 -0.07688 0.50000 6.00000 but all the values are 0(zero) when course==P7A >summary(Master.complete$Yfrm7A[Master.complete$Course=="P7A"]) Min. 1st Qu. Median Mean 3rd Qu. Max. 0 0 0 0 0 0 Thus when I run the following mixed model I get no errors fit.full <- lme(fixed= zGrade ~ Rep + ISE +Yfrm7A+Ufrm7A+Female+White+HSGPA+MATH+AP_TOTAL+Years+Course + Course*Rep + Course*Female +Course*White, random= ~1|SID, data = Master.complete, na.action=na.exclude) but if I add in a Course*Yfrm7A term fit.full <- lme(fixed= zGrade ~ Rep + ISE +Yfrm7A+Ufrm7A+Female+White+HSGPA+MATH+AP_TOTAL+Years+Course + + Course*Rep + Course*Female +Course*White+Course*Yfrm7A, + random= ~1|SID, data = Master.complete, na.action=na.exclude) I get Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 I suspect I could solve this problem with ordering the levels of "Course" so that P7A was the first level and thus the one that others were compared to but I am unclear on how to do so. Robert [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.