Check characteristics of models: whether a model fit
corresponds to a linear (LMM), generalized linear (GLMM),
or nonlinear (NLMM) mixed model, and whether a linear
mixed model has been fitted by REML or not
isREML(x) is always
FALSE for GLMMs and
isREML(x, ...) isLMM(x, ...) isNLMM(x, ...) isGLMM(x, ...)
a fitted model.
additional, optional arguments. (None are used in the merMod methods)
These are generic functions. At present the only methods
are for mixed-effects models of class
a logical value
fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy) gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd), data = cbpp, family = binomial) nm1 <- nlmer(circumference ~ SSlogis(age, Asym, xmid, scal) ~ Asym|Tree, Orange, start = c(Asym = 200, xmid = 725, scal = 350)) isLMM(fm1) isGLMM(gm1) ## check all : is.MM <- function(x) c(LMM = isLMM(x), GLMM= isGLMM(x), NLMM= isNLMM(x)) stopifnot(cbind(is.MM(fm1), is.MM(gm1), is.MM(nm1)) == diag(rep(TRUE,3)))
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.