LogLikeiC: Calculate the ss contributions to the conditional likelihood...

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

Description

Calculate the ss contributions to the conditional likelihood for the univariate and bivariate sampling cases.

Usage

LogLikeiC(subjectData, w.function, beta, sigma0, sigma1, rho, sigmae,
  cutpoints, SampProb)

Arguments

subjectData	a list containing: yi, xi, zi, SampProbi.i
w.function	options include "mean" "intercept" "slope" and "bivar"
beta	mean model parameter p-vector
sigma0	std dev of the random intercept distribution
sigma1	std dev of the random slope distribution
rho	correlation between the random intercept and slope
sigmae	std dev of the measurement error distribution
cutpoints	cutpoints defining the sampling regions. (a vector of length 4 c(xlow, xhigh, ylow, yhigh))
SampProb	Sampling probabilities from within each region (vector of length 2 c(central region, outlying region)).

Value

ss contributions to the conditional log likelihood. This is an internal function used by LogLikeC

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