TSGMM_Ber: Two-Step Generalized Method of Moments, Longitudinal Binary...

In lalondetl/GMM:

Description

This function calculates the Generalized Method of Moments (GMM) parameter estimates and standard errors for longitudinal binary (0/1) responses. This is modeled similarly to a Logistic Regression for Bernoulli responses. The function allows for unbalanced data, meaning subjects can have different numbers of times of observation. Both time-independent covariates and time-dependent covariates can be accommodated. Time-dependent covariates can be handled either by specifying the type of each time-dependent covariate, or by allowing the data to determine appropriate moment conditions through the extended classification method.

Usage

TSGMM_Ber(yvec, subjectID, Zmat, Xmat, Tvec, N, mc = "EC",
  covTypeVec = c(-1))

Arguments

yvec	The vector of responses, ordered by subject, time within subject.
subjectID	The vector of subject ID values for each response.
Zmat	The design matrix for time-independent covariates.
Xmat	The design matrix for time-dependent covariates.
Tvec	The vector of times for each subject.
N	The number of subjects.
mc	The method of identifying appropriate moment conditions, either 'EC' for extended classification (default) or 'Types' for user-identified types.
covTypeVec	The vector indicating the type of each time-dependent covariate, according to the order of the columns of Xmat.

Examples

TSGMM_Ber()

lalondetl/GMM documentation built on May 30, 2019, 11:40 p.m.