Hi, I'm having trouble with glmmPQL from the MASS package. I'm trying to fit a model with a binary response variable, two fixed and two random variables (nested), with a sample of about 200,000 data points. Unfortunately, I'm getting an error message that is difficult to understand without knowing the internals of the glmmPQL function.> model <- glmmPQL(primed ~ log(dist) * role , random = ~ dist | > target.utt / prime.utt , family=binomial(link = "logit"), > data=data.utts, niter=5, verbose = TRUE) > Loading required package: nlme > iteration 1 > iteration 2 > iteration 3 > Error in solve.default(pdMatrix(a, fact = TRUE)) : > system is computationally singular: reciprocal condition > number = 8.65949e-32 > In addition: Warning messages: > 1: Singular precision matrix in level -1, block 4 > 2: Singular precision matrix in level -1, block 4 > 3: Singular precision matrix in level -1, block 4 > 4: Singular precision matrix in level -1, block 4 > 5: Singular precision matrix in level -1, block 4Any suggestions? Will a larger dataset (possible) solve the problem? Thanks David -- David Reitter - ICCS/HCRC, Informatics, University of Edinburgh Blog: http://www.davids-world.com Homepage: http://www.david- reitter.com

Did you try "traceback()"? What do you get? I've had good luck with problems like this in listing the function then using "debug" to review while I walk throught the code line by line. This may not be the issue here, but with "family=binomial", if the model being fit can achieve perfect separation, software of this type might generate error messages similar to what you describe. hope this helps. spencer graves David Reitter wrote:> Hi, > > I'm having trouble with glmmPQL from the MASS package. > I'm trying to fit a model with a binary response variable, two fixed > and two random variables (nested), with a sample of about 200,000 > data points. > > Unfortunately, I'm getting an error message that is difficult to > understand without knowing the internals of the glmmPQL function. > > >>model <- glmmPQL(primed ~ log(dist) * role , random = ~ dist | >>target.utt / prime.utt , family=binomial(link = "logit"), >>data=data.utts, niter=5, verbose = TRUE) >>Loading required package: nlme >>iteration 1 >>iteration 2 >>iteration 3 >>Error in solve.default(pdMatrix(a, fact = TRUE)) : >> system is computationally singular: reciprocal condition >>number = 8.65949e-32 >>In addition: Warning messages: >>1: Singular precision matrix in level -1, block 4 >>2: Singular precision matrix in level -1, block 4 >>3: Singular precision matrix in level -1, block 4 >>4: Singular precision matrix in level -1, block 4 >>5: Singular precision matrix in level -1, block 4 > > > Any suggestions? Will a larger dataset (possible) solve the problem? > > Thanks > David > > -- > David Reitter - ICCS/HCRC, Informatics, University of Edinburgh > Blog: http://www.davids-world.com Homepage: http://www.david- > reitter.com > > ______________________________________________ > R-help at 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