Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
library(mets)
## -----------------------------------------------------------------------------
library(mets)
set.seed(100)
###
n <- 400
kumar <- kumarsim(n,depcens=1)
kumar$cause <- kumar$status
kumar$ttt24 <- kumar[,6]
dtable(kumar,~cause)
dfactor(kumar) <- gp.f~gp
kumar$id <- 1:n
kumar$idc <- sample(100,n,TRUE)
kumar$ids <- sample(n,n)
kumar$id2 <- sample(n,n)
kumar2 <- kumar[order(kumar$id2),]
kumar$int <- interaction(kumar$gp,kumar$dnr)
kumar2$int <- interaction(kumar2$gp,kumar2$dnr)
clust <- 0
b2 <- binregATE(Event(time,cause)~gp.f+dnr+preauto+ttt24,kumar,cause=2,
treat.model=gp.f~dnr+preauto+ttt24,time=40,cens.model=~strata(gp,dnr))
summary(b2)
b5 <- binregATE(Event(time,cause)~int+preauto+ttt24,kumar,cause=2,
treat.model=int~preauto+ttt24,cens.code=0,time=60)
summary(b5)
## -----------------------------------------------------------------------------
ib2 <- logitIPCWATE(Event(time,cause)~gp.f+dnr+preauto+ttt24,kumar,cause=2,
treat.model=gp.f~dnr+preauto+ttt24,time=40,cens.model=~strata(gp,dnr))
summary(ib2)
ib5 <- logitIPCW(Event(time,cause)~gp.f+dnr+preauto+ttt24,kumar,cause=2,cens.code=0,
time=60,cens.model=~strata(gp,dnr))
summary(ib5)
ibs <- logitIPCW(Event(time,cause)~gp.f+dnr+preauto+ttt24,kumar,cause=2,cens.code=0,time=60)
summary(ibs)
check <- 0
if (check==1) {
require(riskRegression)
e.wglm <- wglm( regressor.event=~gp.f+dnr+preauto+ttt24, formula.censor = Surv(time,cause==0)~+1, times = 60, data = kumar, product.limit=TRUE,cause=2)
summary(e.wglm)$coef
estimate(ibs)
es.wglm <- wglm( regressor.event=~gp.f+dnr+preauto+ttt24,
formula.censor = Surv(time,cause==0)~strata(gp,dnr), times = 60,
data = kumar, product.limit=TRUE,cause=2)
summary(es.wglm)$coef
estimate(ib5)
}
## -----------------------------------------------------------------------------
kumar$cause2 <- 1*(kumar$cause==2)
b3 <- logitATE(cause2~gp.f+dnr+preauto+ttt24,kumar,treat.model=gp.f~dnr+preauto+ttt24)
summary(b3)
###library(targeted)
###b3a <- ate(cause2~gp.f|dnr+preauto+ttt24| dnr+preauto+ttt24,kumar,family=binomial)
###summary(b3a)
## calculate also relative risk
estimate(coef=b3$riskDR,vcov=b3$var.riskDR,f=function(p) p[1]/p[2])
## -----------------------------------------------------------------------------
b3 <- normalATE(time~gp.f+dnr+preauto+ttt24,kumar,treat.model=gp.f~dnr+preauto+ttt24)
summary(b3)
## -----------------------------------------------------------------------------
sessionInfo()
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