qrNLMM (version 3.4)

HIV: HIV viral load study

Description

The data set belongs to a clinical trial (ACTG 315) studied in previous researches by Wu (2002) and Lachos et al. (2013). In this study, we analyze the HIV viral load of 46 HIV-1 infected patients under antiretroviral treatment (protease inhibitor and reverse transcriptase inhibitor drugs). The viral load and some other covariates were mesured several times days after the start of treatment been 4 and 10 the minimum and maximum number of measures per patient respectively.

Usage

data(HIV)

Format

This data frame contains the following columns:

patid

a numeric vector indicating the patient register number.

ind

a numeric vector indicating the number patient on which the measurement was made. It represents the subject number in the study.

day

time in days.

cd4

cd4 count in cells/\(mm^{3}\).

lgviral

viral load in log10 scale.

cd8

cd8 count in cells/\(mm^{3}\).

Details

In order to fit the nonlinear data we sugest to use the Nonlinear model proposed by Wu (2002) and also used by Lachos et al. (2013).

Examples

if (FALSE) {
data(HIV)
attach(HIV)

y     = lgviral            #response
x     = day/100            #time
covar = cd4/100            #covariate

#Nonlinear model used in Lachos(2013)

#Full Nonlinear expression
exprNL = expression(log(exp(fixed[1]+random[1])*exp(-(fixed[2]+random[2])*x)+
                    exp(fixed[3]+random[3])*exp(-(fixed[4]+random[4]+fixed[5]
                    *covar[1])*x))/log(10))

#Initial values for fixed effects
initial = c(12,31,6,-2,0.6)

#A median regression (by default)
median_reg = QRNLMM(y,x,ind,initial,exprNL,covar)
}