HIV | R Documentation |
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.
data(HIV)
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}
.
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).
Wu, L. (2002). A joint model for nonlinear mixed-effects models with censoring and covariates measured with error, with application to aids studies. Journal of the American Statistical association, 97(460), 955-964.
Lachos, V. H., Castro, L. M. & Dey, D. K. (2013). Bayesian inference in nonlinear mixed-effects models using normal independent distributions. Computational Statistics & Data Analysis, 64, 237-252.
## Not run:
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)
## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.