Function reference • ELCIC

All functions

ELCIC.gee(): The whole procedure for joint selection of mean structure and correlation structure in longitudinal data without missingness or missing completely at random

ELCIC.gee.single(): Calculate ELCIC value for a given candidate model under GEE framework with complete longitudinal data or data missing completely at random.

ELCIC.glm(): The whole variable selection procedure for mean structure in GLM

ELCIC.glm.single(): Variable selection in generalized linear models (GLM)

ELCIC.wgee(): The whole procedure for joint selection of mean structure and correlation structure for missing longitudinal data under the mechanism of missing at random and drop-out

ELCIC.wgee.single(): Calculate ELCIC value for a given candidate model under WGEE framework for missing longitudinal data under the mechanism of missing at random and drop-out

ELCICgee(): Model selection based on ELCIC under the syntax of GEE (Main function).

ELCICglm(): Variable selection based on ELCIC under the syntax of GLM (Main function).

ELCICwgee(): Model selection based on ELCIC under the syntax of WGEE (Main function).

MLIC.wgee(): The whole MLIC procedure for joint selection of mean structure and correlation structure for missing longitudinal data under the mechanism of missing at random and drop-out

QICW.wgee(): The whole QICW procedure for joint selection of mean structure and correlation structure for missing longitudinal data under the mechanism of missing at random and drop-out

QICc.gee(): Joint selection procedure of marginal mean and correlation structures in longitudinal data based on QIC

cond.prob(): Calculate conditional probabilities for observing records at each time point

ee.gee(): Estimating equation for GEE without missingness or with data missing completely at random.

ee.gee.mean(): Estimating equation of marginal mean for GEE without missingness or missing completely at random

ee.glm(): Estimating equation for ELCIC under GLM

ee.wgee(): Estimating equation for weighted GEE (WGEE) for missing longitudinal data under the mechanism of missing at random and drop-out

ee.wgee.mean(): Estimating equation for marginal mean under WGEE for missing longitudinal data under the mechanism of missing at random and drop-out

gee.generator(): Generate longitudinal data without missingness

geesimdata: Data simulated for model selection under GEE framework without missingness

glm.generator(): Cross-sectional data generation under GLM

glmsimdata: Data simulated for variable selection under GLM framework

impsdata: Inpatient Multidimensional Psychiatric Scale (IMPS)

lambda.find.gee(): Calculate the tuning parameters involved in ELCIC under GEE

lambda.find.gee.mean(): Calculate the tuning parameters under marginal mean selection in GEE

lambda.find.glm(): To calculate tuning parameter involved in ELCIC under GLM

lambda.find.wgee(): Calculate the tuning parameters involved in ELCIC under WGEE with data missing at random

lambda.find.wgee.mean(): Calculate the tuning parameters involved in marginal mean selection under WGEE with data missing at random

marg.prob(): Calculate the inverse of marginal probability for observing records at each time point

respiratorydata: Data from a clinical trial comparing two treatments for a respiratory illness

wgeesimdata: Data simulated for model selection under WGEE framework for missing longitudinal data under the mechanism of missing at random and drop-out.