## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, #dev="png", comment = "#>" ) fullVignette <- Sys.getenv("_R_FULL_VIGNETTE_") %in% c("1","TRUE") library(mets) ## ----------------------------------------------------------------------------- library(mets) runb <- 0 options(warn=-1) set.seed(1000) # to control output in simulatins for p-values below. n <- 200; k.boot <- 10; dat <- kumarsimRCT(n,rho1=0.5,rho2=0.5,rct=2,censpar=c(0,0,0,0), beta = c(-0.67, 0.59, 0.55, 0.25, 0.98, 0.18, 0.45, 0.31), treatmodel = c(-0.18, 0.56, 0.56, 0.54),restrict=1) dfactor(dat) <- dnr.f~dnr dfactor(dat) <- gp.f~gp drename(dat) <- ttt24~"ttt24*" dat$id <- 1:n dat$ftime <- 1 ## ----------------------------------------------------------------------------- weightmodel <- fit <- glm(gp.f~dnr.f+preauto+ttt24,data=dat,family=binomial) wdata <- medweight(fit,data=dat) ## ----------------------------------------------------------------------------- aaMss2 <- binreg(Event(time,status)~gp+dnr+preauto+ttt24+cluster(id),data=dat,time=50,cause=2) summary(aaMss2) ## ----label=firstmodel--------------------------------------------------------- ### binomial regression ########################################################### aaMss <- binreg(Event(time,status)~dnr.f0+dnr.f1+preauto+ttt24+cluster(id),data=wdata, time=50,weights=wdata$weights,cause=2) summary(aaMss) ll <- mediatorSurv(aaMss,fit,data=dat,wdata=wdata) summary(ll) if (runb>0) { bll <- BootmediatorSurv(aaMss,fit,data=dat,k.boot=k.boot); summary(bll)} ## ----label=multiplemodels----------------------------------------------------- ### lin-ying model ################################################################ aaMss <- aalenMets(Surv(time/100,status==2)~dnr.f0+dnr.f1+preauto+ttt24+cluster(id),data=wdata, weights=wdata$weights) ll <- mediatorSurv(aaMss,fit,data=dat,wdata=wdata) summary(ll) if (runb>0) { bll <- BootmediatorSurv(aaMss,fit,data=dat,k.boot=k.boot); summary(bll)} ### cox model ############################################################################### aaMss <- phreg(Surv(time,status==2)~dnr.f0+dnr.f1+preauto+ttt24+cluster(id),data=wdata, weights=wdata$weights) summary(aaMss) ll <- mediatorSurv(aaMss,fit,data=dat,wdata=wdata) summary(ll) if (runb>0) { bll <- BootmediatorSurv(aaMss,fit,data=dat,k.boot=k.boot); summary(bll)} ### Fine-Gray #############################################################3 aaMss <- cifreg(Event(time,status)~dnr.f0+dnr.f1+preauto+ttt24+cluster(id),data=wdata, weights=wdata$weights,propodds=NULL,cause=2) summary(aaMss) ll <- mediatorSurv(aaMss,fit,data=dat,wdata=wdata) summary(ll) if (runb>0) { bll <- BootmediatorSurv(aaMss,fit,data=dat,k.boot=k.boot); summary(bll)} ### logit model #############################################################3 aaMss <- cifreg(Event(time,status)~dnr.f0+dnr.f1+preauto+ttt24+cluster(id),data=wdata, weights=wdata$weights,cause=2) summary(aaMss) ll <- mediatorSurv(aaMss,fit,data=dat,wdata=wdata) summary(ll) if (runb>0) { bll <- BootmediatorSurv(aaMss,fit,data=dat,k.boot=k.boot); summary(bll)} ### binomial outcome ############################ aaMss <- binreg(Event(ftime,status)~dnr.f0+dnr.f1+preauto+ttt24+cluster(id),data=wdata, time=50,weights=wdata$weights,cens.weights=1,cause=2) summary(aaMss) ll <- mediatorSurv(aaMss,fit,data=dat,wdata=wdata) summary(ll) if (runb>0) { bll <- BootmediatorSurv(aaMss,fit,data=dat,k.boot=k.boot); summary(bll)} ## ----label=multinom, cache=TRUE, eval=fullVignette---------------------------- # data(tTRACE) # dcut(tTRACE) <- ~. # # weightmodel <- fit <- mlogit(wmicat.4 ~agecat.4+vf+chf,data=tTRACE,family=binomial) # wdata <- medweight(fit,data=tTRACE) # # aaMss <- binreg(Event(time,status)~agecat.40+ agecat.41+ vf+chf+cluster(id),data=wdata, # time=7,weights=wdata$weights,cause=9) # summary(aaMss) # MultMed <- mediatorSurv(aaMss,fit,data=tTRACE,wdata=wdata) ## ----results="hide", echo=FALSE----------------------------------------------- ## To save time building the vignettes on CRAN, we cache time consuming computations if (fullVignette) { MultMed[c('iid','iid.w','iid.surv')] <- NULL saveRDS(MultMed, "data/MultMed.rds") } else { MultMed <- readRDS("data/MultMed.rds") } ## ----------------------------------------------------------------------------- summary(MultMed) ## ----------------------------------------------------------------------------- sessionInfo()