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

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

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.