These functions are exported and documented for use by other packages. They are not intended for end users.
mclogit.fit(y, s, w, X, start = NULL, offset = NULL, control = mclogit.control())mclogit.fit.rePQL(y, s, w, X, Z, start = NULL, start.theta = NULL,
offset = NULL, control = mclogit.control())
a response vector. Should be binary.
a vector identifying individuals or covariate strata
a vector with observation weights.
a model matrix; required.
the random effects design matrix.
an optional numerical vector of starting values for the coefficients.
an optional numerical vector of starting values for the variance parameters.
an optional model offset. Currently only supported for models without random effects.
a list of parameters for the fitting process.
See mclogit.control
A list with components describing the fitted model.