li.lme.score2: Subject specific contribution to the lme model score (also...

In schildjs/ods4lda: Outcome Dependent Sampling (ODS) Designs for Linear Mixed Models Data Analysis

Description

Subject specific contribution to the lme model score (also returns marginal Vi=Cov(Y|X))

Usage

li.lme.score2(subjectData, beta, sigma.vc, rho.vc, sigma.e)

Arguments

subjectData	a list that contains yi, xi, zi, Weights.i. Note that Weights.i is used for inverse probability weighting only.
beta	mean model parameter p-vector
sigma.vc	vector of variance components on standard deviation scale
rho.vc	vector of correlations among the random effects. The length should be q choose 2
sigma.e	std dev of the measurement error distribution

Value

Subject specific contribution to the log-likelihood score (also returns marginal Vi=Cov(Y|X))

schildjs/ods4lda documentation built on March 16, 2020, 8:16 a.m.