UTIdata: Data set for Unstructured Treatment Interruption Study

In fernandalschumacher/tlmec: Linear Student-t Mixed-Effects Models with Censored Data

Data set for Unstructured Treatment Interruption Study

Description

Data set from a study of Unstructured Treatment Interruption in HIV-infected adolescents in four institutions in the US. The main outcome is the HIV-1 RNA viral load, which is subject to censoring below the lower limit of detection of the assay (50 copies/mL). The censored observations are indicated by the variable RNAcens

Usage

data(UTIdata)

Format

A data frame with 146 observations on the following 5 variables.

Patid

patient ID

Days.after.TI

days after treatment interruption

Fup

follow-up months

RNA

viral load RNA

RNAcens

censoring indicator for viral load

References

Saitoh, A., Foca, M, et al. (2008), Clinical outcome in perinatally acquired HIV-infected children and adolescents after unstructured treatment interruption, Pediatrics,121, e513-e521.

Examples

## Not run:  
## load data
data(UTIdata)

## Sort the data by Patient and  visit
o <- order(UTIdata$Patid, UTIdata$Fup)
UTIdata <- UTIdata[o,]

## Create censure vector
cens = (UTIdata$RNAcens==1)+0

## Generate response vector 
y = log10(UTIdata$RNA)
aa=y[cens==0]

## Create the design matrices

x = cbind((UTIdata$Fup==0)+0, (UTIdata$Fup==1)+0, (UTIdata$Fup==3)+0, 
          (UTIdata$Fup==6)+0, (UTIdata$Fup==9)+0, (UTIdata$Fup==12)+0, 
          (UTIdata$Fup==18)+0, (UTIdata$Fup==24)+0)
z = matrix(rep(1, length(y)), ncol=1)
cluster = as.numeric(UTIdata$Patid)

## Create the nj vector
nj<-matrix(0,72,1)
for (j in 1:72) {
nj[j]=sum(cluster==j)
}

## Number of individuals  
m<-dim(nj)[1]

## Call the tlmec with Normal mixed-effects 
out.N <- tlmec(cens,y,x,z,nj,family="Normal",criteria=TRUE)

## Call the tlmec with Student-t mixed-effects 
out.T <- tlmec(cens,y,x,z,nj,nu=9,family="t",criteria=TRUE)

## End(Not run)

fernandalschumacher/tlmec documentation built on May 27, 2022, 10:10 p.m.