Error messages using LMER
On 8/18/05, Shige Song <shigesong at gmail.com> wrote:
Dear All, After playing with lmer for couple of days, I have to say that I am amazed! I've been using quite some multilevel/mixed modeling packages, lme4 is a strong candidate for the overall winner, especially for multilevel generzlized linear models. Now go back to my two-level poisson model with cross-classified model. I've been testing various different model specificatios for the past couple of days. Here are the models I tried: 1) Two level random intercept model with level-1 covariates only m1 <- lmer(.D ~ offset(log(.Y)) + (1|provn) +(1|bcohort) + x1 + x2 , data, poisson, method="Laplace") 2) Two-level random intercept model with both level-1 and level-2 covariates, but no cross-level interactions: m2 <- lmer(.D ~ offset(log(.Y)) + (1|provn) +(1|bcohort) + x1 + x2 + z1 + z2, data, poisson, method="Laplace") 3) Two-level random intercept with cross-level interaction m3 <- lmer(.D ~ offset(log(.Y)) + (1|provn) +(1|bcohort) + x1 + x2 + z1 + z2 + x1:z1 + x2:z2, data, poisson, method="Laplace") Both model 1 and 2 run fine. For model 3, I got error message: ---------------------------------- Error in fn(par, ...) : Unable to invert singular factor of downdated X'X In addition: Warning messages: 1: optim or nlminb returned message ERROR: ABNORMAL_TERMINATION_IN_LNSRCH in: LMEopt(x = mer, value = cv) 2: Leading minor of size 1 of downdated X'X is indefinite ---------------------------------- What is going on here? Any workarounds? Thanks!
The first thing I would try is set the EMverbose and msVerbose flags in the control list to see what occurs within the optimization. That is append the argument control = list(EMverbose = TRUE, msVerbose = TRUE) to your call to lmer(). You may also want to try the call in a recently compiled R-devel, which will be released as R-2.2.0 in October. You will notice that the first warning message reads "optim or nlminb". In R-2.1.1 lmer uses optim for the optimization. Starting with R-2.2.0 the default is to use nlminb. Test compilations of R-devel for Windows are available from CRAN.