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())mmclogit.fitPQL(y, s, w, X, Z, G, groups, start,
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.
a list of design matrices for the (co-)variance parameters.
a list of grouping factors.
an optional numerical vector of starting values for the coefficients.
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.