search for: devcomp

...y(lmer.mod)$AICtab[2][1]) ? mod.data$logLik = as.numeric(summary(lmer.mod)$AICtab[3][1]) ? mod.data$deviance = as.numeric(summary(lmer.mod)$AICtab[4][1]) ? mod.data$df.resid = as.numeric(summary(lmer.mod)$AICtab[5][1]) ? #add number of datapoints ? mod.data$N = as.numeric(summary(incr.best.m)$devcomp$dims[1]) ? #add model name ? mod.data$model = name ? return(mod.data) } lmer.ranef.data.extract = function(lmer.mod, name=deparse(substitute(lmer.mod))){ ? #extract random effect variance, standard error, correlations between slope and intercept ? mod.data.ef = as.data.frame(VarCorr(lme...

I can't find a way to retrieve z values and p-values from the output from lmer in the lme4 package. How is this done? Rick B.

Hi, I have been having a tedious issue with lmer models with lots of factors and lots of levels. In order to get the basic information at the beginning of the print out I also have to generate these enormous tables as well. Is there a method command to leave off all of the effects and correlations? Or, do I have to go to string commands?

Hello All, I would like to retrieve some of the results from the lmer(...) function in library lme4. If I run a model, say fm.1 <- lmer(y ~ 1 + (1 | x), data = dog) and try names(fm.1), I get NULL. Is there anyway to retrieve the information? Thanks

...variance <- quote(family$variance(mu)) dev.resids <- quote(family$dev.resids(Y, mu, weights)) LMEopt <- get("LMEoptimize<-") doLMEopt <- quote(LMEopt(x = mer, value = cv)) if (family$family %in% c("binomial", "poisson")) mer at devComp[8] <- -1 mer at status["glmm"] <- as.integer(switch(method, PQL = 1, Laplace = 2, AGQ = 3)) GSpt <- .Call(glmer_init, environment(), fltype) if (cv$usePQL) { .Call(glmer_PQL, GSpt) PQLpars <- c(fixef(mer), .Call(mer_coef, mer, 2)) }...

Three related questions on LMEs and GLMMs in R: (1) Is there a way to fix the dispersion parameter (at 1) in either glmmPQL (MASS) or GLMM (lme4)? Note: lme does not let you fix any variances in advance (presumably because it wants to "profile out" an overall sigma^2 parameter) and glmmPQL repeatedly calls lme, so I couldn't see how glmmPQL would be able to fix the dispersion

...;S3",..: 1 1 1 1 1 2 2 2 2 2 ... .. ..- attr(*, "assign")= int 1 ..@ cnms :List of 1 .. ..$ Subject: chr "(Intercept)" ..@ lower : num 0 ..@ theta : num 0.499 ..@ beta : num [1:4] 512.6 -20.5 -24.2 31.7 ..@ u : num [1:4] 3.97 -12.4 -6.62 15.04 ..@ devcomp:List of 2 .. ..$ cmp : Named num [1:10] 3.24 5.56 3862.92 439.6 4302.51 ... .. .. ..- attr(*, "names")= chr [1:10] "ldL2" "ldRX2" "wrss" "ussq" ... .. ..$ dims: Named int [1:12] 20 20 4 16 1 4 1 1 0 4 ... .. .. ..- attr(*, "names")...

Javier, Creo que aquí aplica la ley de Linus que dice: "Dado un número suficientemente elevado de ojos, todos los errores se convierten en obvios". La persona que revisa y encuentra un error no necesariamente tiene que ser la misma que la que lo escribe. Una motivación muy importante al compartir un código es la de recibir los beneficios del control de calidad por parte de tus pares.

...t; .. ..- attr(*, "assign")= int 1 > ..@ cnms :List of 1 > .. ..$ Subject: chr "(Intercept)" > ..@ lower : num 0 > ..@ theta : num 0.499 > ..@ beta : num [1:4] 512.6 -20.5 -24.2 31.7 > ..@ u : num [1:4] 3.97 -12.4 -6.62 15.04 > ..@ devcomp:List of 2 > .. ..$ cmp : Named num [1:10] 3.24 5.56 3862.92 439.6 4302.51 ... > .. .. ..- attr(*, "names")= chr [1:10] "ldL2" "ldRX2" "wrss" "ussq" ... > .. ..$ dims: Named int [1:12] 20 20 4 16 1 4 1 1 0 4 ... > .. .. ..- attr(*...