logACi2q: Log of the Ascertainment correction piece for bivariate...

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

Description

Calculate the log transformed ascertainment correction under a bivariate Q_i. Also return vi

Calculate the log transformed ascertainment correction under a bivariate Q_i. Also return vi

Usage

logACi2q(yi, xi, zi, wi, beta, sigma.vc, rho.vc, sigma.e, cutpoints,
  SampProb)

logACi2q(yi, xi, zi, wi, beta, sigma.vc, rho.vc, sigma.e, cutpoints,
  SampProb)

Arguments

yi	n_i-response vector
xi	n_i by p design matrix for fixed effects
zi	n_i by 2 design matric for random effects (intercept and slope)
wi	the pre-multiplier of yi to generate the sampling variable q_i
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
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)).
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
yi	n_i-response vector
xi	n_i by p design matrix for fixed effects
zi	n_i by q design matric for random effects (intercept and slope)
wi	the pre-multiplier of yi to generate the sampling variable q_i
beta	mean model parameter p-vector
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

log transformed ascertainment correction

log transformed ascertainment correction

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