search for: contraception

...ar list members, In re-running with GLMM() from the lme4 package a generalized-linear mixed model that I had previously fit with glmmPQL() from MASS, I'm getting a warning of a convergence failure, even when I set the method argument of GLMM() to "PQL": > bang.mod.1 <- glmmPQL(contraception ~ as.factor(children) + cage + urban, + random=~as.factor(children) + cage + urban|district, + family=binomial, data=Bangladesh) # works! > bang.mod.1 <- GLMM(contraception ~ as.factor(children) + cage + urban, + random=~as.factor(children) + cage + urban|district, + family=...

...39; which comes from nr.B20C (it has values 0 or 1). This inconvenient as I would like to have ultimately the following table pharm No Yes no resp 716 7 6 (FROM nr.B20C where row has value 1). Background. The variable pharm assess where you used the pharmacy to get your contraception. Pancho Mulongeni Research Assistant PharmAccess Foundation 1 Fouch? Street Windhoek West Windhoek Namibia ? Tel:?? +264 61 419 000 Fax:? +264 61 419 001/2 Mob: +264 81 4456 286

Dear list members, I'm interested in showing that within-group statistical dependence is negligible, so I can use ordinary linear models without including random effects. However, I can find no mention of testing a model with vs. without random effects in either Venable & Ripley (2002) or Pinheiro and Bates (2000). Our in-house statisticians are not familiar with this, either,

Hi, I am using lmer (from the package lme4) to predict a binary response variable (REL) from a bunch of fixed effects and two random effects (Speaker_ID and NPhead_lemma): fit <- lmer(REL ~ SPEAKER_GENDER + log(SPEECHRATE) + SQSPEECHRATE + ..... + (1|Speaker_ID) + (1|NPhead_lemma), family="binomial", data=data.lmer, method="Laplace", model=T, x=T) I

Is the battery old? PbAc ones usually last for 2-3 years and then degrade. Should be a field-replaceable part. Some 20 years ago I had an APC BackUPS become a glorified power strip every few years, so when the wall power disappeared - load went down immediately. It was also beeping about battery replacement (but in the closet, was not often noticed quickly). This is also a way for you to check if

Dear list, I am trying to use MuMIn to compare all possible mixed models using the dredge function on binomial data but I am getting an error message that I cannot decode. This error only occurs when I use glmer. When I use an lmer analysis on a different response variable every works great. Example using a simplified glmer model global model: mod<- glmer(cbind(st$X2.REP.LIVE,