MMLongit {binaryMM} R Documentation

## Function used to fit marginalized models

### Description

Main function used to fit marginalized models. See mm() for a more user-friendly function and examples

### Usage

MMLongit(
params,
id,
X,
Y,
Xgam,
Xsig,
Q,
weight = rep(1, length(Y)),
offset = rep(0, length(Y)),
stepmax = 1,
steptol = 1e-06,
hess.eps = 1e-07,
verbose = FALSE,
iterlim
)


### Arguments

 params a vector of initial values. id a vector of cluster identifiers. X a design matrix, including intercept, for the mean formula. Y a binary vector Xgam a design matrix for the transition formula. Xsig a design matrix for the latent variable formula. Q a scalar denoting the number of quadrature points. weight a vector of sampling weights. offset an optional offset term. stepmax a scalar steptol a scalar hess.eps a scalar AdaptiveQuad an indicator if adaptive quadrature is to be used. NOT CURRENTLY IMPLEMENTED. verbose an indicator if model output should be printed to the screen during maximization (or minimization of negative log-likelihood). See print.level in nlm. iterlim a scalar to denote the maximum iteration limit used by nlm. Default value is 100

### Value

This function returns marginal parameters (beta) and dependence parameters (alpha) along with the associated covariance matrices.

[Package binaryMM version 0.1.1 Index]