glmm-class {lme4} | R Documentation |
A generalized linear mixed-effects model.
Objects can be created by calls of the form new("glmm", ...)
but more commonly they are created by calls to GLMM
.
family
:"family"
, specifying
the error distribution and the link function used in the model.origy
:"numeric"
, the original
response.n
:"numeric"
, if the family is
binomial
, the number of observations for each data point.prior.weights
:"numeric"
,
weights used when creating the model.frame.init.weights
:"numeric"
,
weights from a fixed effects generalized linear model for the data.init.y
:"numeric"
, the linear
predictor from a fixed effects generalized linear model for the data.method
:"character"
, the method
used to fit the generalized linear mixed model.reStruct
:"reStruct"
, from class
"lme"
, the random-effects structure for the model.frame
:"data.frame"
, from class
"lme"
, the model.frame used to fit the model.na.action
:"ANY"
, from class
"lme"
, the na.action
argument used when creating the
model.frame
.fitted
:"numeric"
, from class
"lme"
, the fitted values in the linear predictor scale.call
:"call"
, from class
"lme"
, the function call used to create the object.
Class "lme"
, directly.
signature(x = "glmm", value = "list")
:
optimize the PQL approximation to the log-likelihood.signature(x = "glmm")
: Extract variance and correlation components.signature(object = "glmm", value = "numeric")
:
assign the fixed effects (used for method = "Laplace"
).signature(object = "glmm")
: extract the response.signature(object = "glmm")
: extract the
(approximate) log-likelihood.signature(object = "glmm")
: show the object.signature(object = "glmm")
: summarize the object.Saikat DebRoy saikat@stat.wisc.edu and Douglas Bates bates@stat.wisc.edu
library(lme4) data(guImmun) # This returns an object of class glmm fm = GLMM(immun ~ kid2p + mom25p + ord + ethn + momEd + husEd + momWork + rural + pcInd81, data = guImmun, family = binomial, random = ~1|comm/mom) fm