tlmec (version 0.0-2)

UTIdata: 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)