search for: saveb

...(M1) (Intercept) log(sigma^2) log(grop.(In)) [1,] 9.099073 0.5711817 3.246981 attr(,"mcpar") [1] 1 1 1 attr(,"class") [1] "mcmc" > mcmcsamp(M2) Error: inconsistent degrees of freedom and dimension Error in t(.Call("mer_MCMCsamp", object, saveb, n, trans, PACKAGE = "Matrix")) : unable to find the argument 'x' in selecting a method for function 't' -- Andrew Gelman Professor, Department of Statistics Professor, Department of Political Science gelman at stat.columbia.edu www.stat.columbia.edu/~gelman...

...<2>>= require(lme4) gl.lmer <- lmer(rounds ~ method * physique + (1 | physique/team), data = gunload) mcmcsamp(gl.lmer) @ lmer runs as expected, but mcmcsamp() gives: Error: Leading minor of order 1 in downdated X'X is not positive definite Error in t(.Call(mer_MCMCsamp, object, saveb, n, trans, verbose, deviance)) : error in evaluating the argument 'x' in selecting a method for function 't' I tried: <<3>>= require(nlme) gl.lme <- lme(rounds ~ method * physique, random = ~1 | physique/ team, data = gunload) @ which gave all the expected out...

Thanks to some help by Doug Bates (and the updated version of the Matrix package), I've refined my question about fitting nested and non-nested factors in lmer(). I can get it to work in linear regression but it crashes in logistic regression. Here's my example: # set up the predictors n.age <- 4 n.edu <- 4 n.rep <- 100 n.state <- 50 n <- n.age*n.edu*n.rep age.id

I really hope sombody could help me with the following, I'm having problems accessing the random effect samples following the example on MCMCsamp: (fm1 <- lmer(Reaction ~ Days + (1|Subject) + (0+Days|Subject), sleepstudy)) set.seed(101); samp0 <- mcmcsamp(fm1, n = 1000, saveb=TRUE) str(samp0) Formal class 'merMCMC' [package "lme4"] with 9 slots ..@ Gp : int [1:3] 0 18 36 ..@ ST : num [1:2, 1:1000] 0.98 0.234 1.097 0.258 0.915 ... ..@ call : language lmer(formula = Reaction ~ Days + (1 | Subject) + (0 + Days | Subject), da...

Dear All, I am working with linear mixed-effects models using the lme4 package in R. I created a model with the lmer function including some main effects, a two-way interaction and a random effect. Now I am searching how I could incorporate an interaction between the random effect and one of the fixed effects. I tried to express the interaction in: