MMLongit {binaryMM}

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,
  AdaptiveQuad = FALSE,
  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.