# getJMDL: Extract or Get Generalized Components from a Fitted Joint... In jmdl: Joint Mean-Correlation Regression Approach for Discrete Longitudinal Data

## Description

Extract (or "get") "components" - in a generalized sense - from a fitted joint mean correlation model from an object of class "JmdlMod".

## Usage

 ```1 2 3 4 5 6``` ```getJMDL(object, name) ## S3 method for class 'jmdlMod' getJMDL(object, name = c("m", "Y", "X", "W", "offset", "theta", "beta", "gamma", "delta", "loglik", "family", "q", "time", "stdbeta", "stdgamma", "stddelta")) ```

## Arguments

 `object` a fitted joint mean correlation model of class "JmdlMod", i.e., typically the result of jmdl(). `name` a character vector specifying the name(s) of the "component". possible values are: `"m"`a vector of number of measurement for each subject `"Y"`response matrix `"X"`model matrix for mean structure `"W"`model matrix for correlation structure (the lower triangular matrix) `"offset"`a vecter to be added to a linear predictor `"theta"`parameter estimates of joint mean correlation model `"beta"`parameter estimates for mean structure model `"delta"`parameter estimates for mean structure model (for Nbinom model) `"gamma"`parameter estimates for correlation structure (the lower triangular matrix) `"stdbeta"`standard error for parameter beta `"stddelta"`standard error for parameter delta `"stdgamma"`standard error for parameter gamma `"loglik"`log-likelihood, except for a constant `"family"`the marginal distributions of the discrete variables `"q"`degree of polynomial of the time lag to model the lower triangular matrix `"time"`a vector of time from the data

## Methods (by class)

• `jmdlMod`: Extract or Get Generalized Components from a Fitted Joint Mean Correlation Model

## Examples

 ```1 2 3 4 5 6``` ```mydat <- toydata fit <- jmdl(Y|id|time ~ X, data = mydat, q = 2, family ='Bernoulli') beta <- getJMDL(fit, "beta") beta loglik <- getJMDL(fit, "loglik") loglik ```

jmdl documentation built on May 2, 2019, 11:04 a.m.