# R/frailty.t.R In survival: Survival Analysis

#### Documented in frailty.t

```# \$Id: frailty.t.S 11377 2009-12-14 22:59:56Z therneau \$
#
# Defining function for t-distribution frailty fits
#
frailty.t <- function(x, sparse=(nclass>5), theta, df, eps= 1e-5,  tdf=5,
method=c("aic", "df", "fixed"), ...) {
nclass <- length(unique(x[!is.na(x)]))
if (sparse){
x <-as.numeric(factor(x))
class(x) <- "coxph.penalty"
}
else{
x <- factor(x)
class(x) <- c("coxph.penalty",class(x))
attr(x,'contrasts') <- contr.treatment(nclass, contrasts=FALSE)
}

if (tdf <=2) stop("Cannot have df <3 for the t-frailty")
# Check for consistency of the arguments
if (missing(method)) {
if (!missing(theta)) {
method <- 'fixed'
if (!missing(df))
stop("Cannot give both a df and theta argument")

}
else if (!missing(df)) {
if (df==0) method <- 'aic'
else       method <- 'df'
}
}
method <- match.arg(method)
if (method=='df' && missing(df)) stop("Method = df but no df argument")
if (method=='fixed' && missing(theta))
stop("Method= fixed but no theta argument")
if (method !='fixed' && !missing(theta))
stop("Method is not 'fixed', but have a theta argument")

pfun<- function(coef, theta, ndead, tdf){
if (theta==0) list(recenter=0, penalty=0, flag=TRUE)
else {
sig <- theta* (tdf-2)/tdf  #scale contant^2 in density formula
#
# Find the centering constant, using 1 NR step
#
temp  <- 1 + coef^2/(tdf*sig)
temp1 <- coef/temp
temp2 <- 1/temp - (2/(tdf*sig))*coef^2/temp^2
recenter <- sum(temp1)/sum(temp2)  #NR step towards MLE

coef <- coef - recenter
const <- (tdf+1)/(tdf*sig)
temp  <- 1 + coef^2/(tdf*sig)
list(recenter=recenter,
first=   const*coef/temp,
second=  const*(1/temp - (2/(tdf*sig))*coef^2/temp^2),
penalty= sum(.5*log(pi*tdf*sig) + ((tdf+1)/2)*log(temp) +
lgamma(tdf/2) - lgamma((tdf+1)/2)),
flag=FALSE)
}
}

printfun <- function(coef, var, var2, df, history) {
if (!is.null(history\$history))
theta <- history\$history[nrow(history\$history),1]
else theta <- history\$theta

if (is.matrix(var)) test <- coxph.wtest(var, coef)\$test
else 		    test <- sum(coef^2/var)
df2 <- max(df, .5)      # Stop silly p-values
list(coef=c(NA, NA, NA, test, df, pchisq(test, df2, lower.tail=FALSE)),
history=paste("Variance of random effect=", format(theta)))
}
# The final coxph object will contain a copy of printfun.  Stop it from
#   also containing huge unnecessary variables, e.g. 'x', known at this
#   point in time.  Not an issue for pfun, which does not get saved.
# The reason for using the survival namespace instead of globalenv() is
# that we call coxph.wtest, which may not be visible outside the name space
environment(printfun) <- asNamespace('survival')

if (method=='fixed') {
temp <- list(pfun=pfun, pparm=tdf,
printfun=printfun,
diag =TRUE,
sparse= sparse,
cfun = function(parms, iter, old){
list(theta=parms\$theta, done=TRUE)},
cparm= list(theta=theta, ...))
}

else if (method=='aic') {
temp <- list(pfun=pfun, pparm=tdf,
printfun=printfun,
diag =TRUE,
sparse= sparse,
cargs = c("neff", "df", "plik"),
cparm=list(lower=0, init=c(.1,1), eps=eps, ...),
cfun = frailty.controlaic)
}
else {  #df method
if (missing(eps)) eps <- .1
temp <- list(pfun=pfun, pparm=tdf,
printfun=printfun,
diag =TRUE,
sparse= sparse,
cargs= c('df'),
cparm=list(df=df, eps=eps, thetas=0, dfs=0,
guess=3*df/length(unclass(x)), ...),
cfun = frailty.controldf)
}

# If not sparse, give shorter names to the coefficients, so that any
#   printout of them is readable.
if (!sparse) {
vname <- paste("t", levels(x), sep=':')
temp <- c(temp, list(varname=vname))
}
attributes(x) <- c(attributes(x), temp)
x
}

```

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survival documentation built on Aug. 24, 2021, 5:06 p.m.