R: Fitting GLMs with Missing Data in Both Responses and Covariates

# Fitting GLMs with Missing Data in Both Responses and Covariates

## Documentation for package ‘glmfitmiss’ version 2.1.0

- DESCRIPTION file

## Help Pages

glmFitMiss-package | glmfitmiss: Fitting Binary Regression Models with Missing Data
glmfitmiss-package | glmfitmiss: Fitting Binary Regression Models with Missing Data
emBinRegMAR | Fitting binary regression with missing categorical covariates using Expectation-Maximisation (EM) based method
emBinRegMixedMAR | Fits binary regression models with both nonignorable missing responses and missing categorical covariates.
emBinRegNonIG | Fitting binary regression with missing responses that are nonignorable based on Ibrahim and Lipsitz (1996)
emforbeta | Fitting binary regression with missing categorical covariates using likelihood based method
emil | Fitting binary regression model with missing responses based on Ibrahim and Lipsitz (1996)
emyxmiss | Fitting generalized linear models with Incomplete data
est | EST data - Eastern Cooperative Oncology Group clinical trials, EST 2282
est45 | EST data - Eastern Cooperative Oncology Group clinical trials, EST 2282
felinedata | felinedata - Chlamydial Infection in Cats
glmfitmiss | glmfitmiss: Fitting Binary Regression Models with Missing Data
ibrahim | ibrahim data - Ibrahim (1990) JASA
incontinence | incontinence- incontinence Data taken from brlrmr pacakge
llkmiss | Fitting binary regression with missing categorical covariates using new likelihood based method that does not require EM algorithm
logRegMAR | Fitting binary regression with missing categorical covariates using new likelihood based method
meningitis | meningitis- Meningococcal Disease Data with missing data in the response variable
meningitis60ymis | meningitis60ymis- Meningococcal Disease Data with missing data in the response variable
metastmelanoma | metastmelanoma - metastatic melanoma trial data
simulateCovariateData | Simulate data with independent categorical covariates
simulateData | Simulate data based on an input covariate data
simulateMissDfYorX | Simulate missing covariate or missing responses data based on an input covariate data
sixcitydata | sixcitydata - A very well published Six city data published in many articles including Ware et al (1984), Ibrahim and Lipsitz (1996). Also avaialble in LogXact User Manual. The dataset is a longitudinal study of the health effects of air pollution (ware et al., 1984).
testyxm | Simulated Test Data - 'testyxm'