Internal functions used for model fit. — mclogit.fit • mclogit

These functions are exported and documented for use by other packages. They are not intended for end users.

Usage

mclogit.fit(y, s, w, X,
            dispersion=FALSE,
            start = NULL, offset = NULL,
            control = mclogit.control())

mmclogit.fitPQLMQL(y, s, w, X, Z, d, 
                   start = NULL,
                   start.Phi = NULL,
                   start.b = NULL,
                   offset = NULL, method=c("PQL","MQL"),
                   estimator = c("ML","REML"),
                   control = mmclogit.control())

Arguments

y: a response vector. Should be binary.
s: a vector identifying individuals or covariate strata
w: a vector with observation weights.
X: a model matrix; required.
dispersion: a logical value or a character string; whether and how a dispersion parameter should be estimated. For details see dispersion.
Z: the random effects design matrix.
d: dimension of random effects. Typically $d=1$ for random intercepts only, $d>1$ for models with random intercepts.
start: an optional numerical vector of starting values for the coefficients.
offset: an optional model offset. Currently only supported for models without random effects.
start.Phi: an optional matrix of strarting values for the (co-)variance parameters.
start.b: an optional list of vectors with starting values for the random effects.
method: a character string, either "PQL" or "MQL", specifies the type of the quasilikelihood approximation.
estimator: a character string; either "ML" or "REML", specifies which estimator is to be used/approximated.
control: a list of parameters for the fitting process. See mclogit.control

Value

A list with components describing the fitted model.