R/svycox.R

In jstable: Create Tables from Different Types of Regression

#' @title svycoxph.display: table for svycoxph.object in survey package.
#' @description Table for complex design cox model.
#' @param svycoxph.obj svycoxph.object
#' @param decimal digit, Default: 2
#' @return List including table, metric, caption
#' @details DETAILS
#' @examples 
#'  library(survival);data(pbc)
#'  pbc$sex = factor(pbc$sex)
#'  pbc$stage = factor(pbc$stage)
#'  pbc$randomized<-with(pbc, !is.na(trt) & trt>0)
#'  biasmodel<-glm(randomized~age*edema,data=pbc,family=binomial)
#'  pbc$randprob<-fitted(biasmodel)
#'  
#'  if (is.null(pbc$albumin)) pbc$albumin<-pbc$alb ##pre2.9.0
#'  
#'  dpbc <- survey::svydesign(id=~1, prob=~randprob, strata=~edema, data=subset(pbc,randomized))
#'  
#'  model <- survey::svycoxph(Surv(time,status>0)~ sex + protime + albumin + stage,design=dpbc)
#'  svycox.display(model)
#' @seealso 
#'  \code{\link[survey]{svycoxph}}
#'  \code{\link[stats]{AIC}}
#' @rdname svycox.display
#' @export 
#' @importFrom survey svycoxph
#' @importFrom stats AIC update
 

svycox.display <- function(svycoxph.obj, decimal = 2){
  
  model <- svycoxph.obj
  if(!any(class(model)=="svycoxph")){stop("Model not from Survey cox model")}
  xf <- attr(model$terms, "term.labels")
  formula.surv <- as.character(model$formula)[2]
  design.model <- model$survey.design
  
  if(length(xf) == 1){
    uni.res <- data.frame(summary(model)$coefficients)
    #uni.res <- data.frame(summary(survey::svycoxph(as.formula(paste(formula.surv, "~", xf, sep="")), design = design.model))$coefficients)
    names(uni.res)[ncol(uni.res)] <- "p"
    uni.res2 <- uni.res[, c("coef", grep("se", colnames(uni.res), value = T)[length(grep("se", colnames(uni.res)))], "z", "p")]
    
    fix.all = coxExp(uni.res2, dec = decimal)
    colnames(fix.all) <- c("HR(95%CI)", "P value")
    #rownames(fix.all) = ifelse(mtype == "frailty", names(model$coefficients)[-length(model$coefficients)], names(model$coefficients))
    rownames(fix.all) <-  names(model$coefficients)
    } else {
    unis <- lapply(xf, function(x){
      uni.res <- data.frame(summary(stats::update(model, formula(paste(paste(c(". ~ .", xf), collapse=' - '), " + ", x)), design = design.model))$coefficients)
      names(uni.res)[ncol(uni.res)] <- "p"
      uni.res2 <- uni.res[, c("coef", grep("se", colnames(uni.res), value = T)[length(grep("se", colnames(uni.res)))], "z", "p")]
      return(uni.res2)
    })
    
   unis2 <- Reduce(rbind, unis)
   uni.res <- unis2
    mul.res <- data.frame(summary(model)$coefficients)
    uni.res <- uni.res[rownames(uni.res) %in% rownames(mul.res), ]  ## set
    colnames(mul.res)[ncol(mul.res)] <- "p"
    fix.all <- cbind(coxExp(uni.res, dec = decimal), coxExp(mul.res[rownames(uni.res), names(uni.res)], dec = decimal))
    colnames(fix.all) <- c("crude HR(95%CI)", "crude P value", "adj. HR(95%CI)", "adj. P value")
    rownames(fix.all) <- rownames(uni.res)
    }
  
  ## rownames
  fix.all.list <- lapply(xf, function(x){fix.all[grepl(x, rownames(fix.all)),]})      
  varnum.mfac <- which(lapply(fix.all.list, length) > ncol(fix.all))
  lapply(varnum.mfac, function(x){fix.all.list[[x]] <<- rbind(rep(NA, ncol(fix.all)), fix.all.list[[x]])})
  fix.all.unlist <- Reduce(rbind, fix.all.list)
  
  rn.list <- lapply(xf, function(x){rownames(fix.all)[grepl(x, rownames(fix.all))]})
  varnum.2fac <- which(xf %in% names(model$xlevels)[lapply(model$xlevels, length) == 2])
  lapply(varnum.2fac, function(x){rn.list[[x]] <<- paste(xf[x], ": ", model$xlevels[[xf[x]]][2], " vs ", model$xlevels[[xf[x]]][1], sep="")})
  lapply(varnum.mfac, function(x){rn.list[[x]] <<- c(paste(xf[x],": ref.=", model$xlevels[[xf[x]]][1], sep=""), gsub(xf[x],"   ", rn.list[[x]]))})
  if (class(fix.all.unlist)[1] == "character"){
    fix.all.unlist <- t(data.frame(fix.all.unlist))
  }
  rownames(fix.all.unlist) <- unlist(rn.list)
  pv.colnum <- which(colnames(fix.all.unlist) %in% c("P value", "crude P value", "adj. P value"))
  for (i in pv.colnum){
    fix.all.unlist[, i] <- ifelse(as.numeric(fix.all.unlist[, i]) < 0.001, "< 0.001", round(as.numeric(fix.all.unlist[, i]), decimal + 1))
  }
  

  ## metric
  no.obs <- model$n
  no.event <- model$nevent
  
  ## From survey package
  extractAIC.svycoxph<-function (fit, scale, k = 2, ...) 
  {
    Delta<-solve(fit$inv.info, fit$var)
    deltabar <- mean(diag(Delta))
    d <- -2*fit$ll[1]
    c(eff.p = sum(diag(Delta)), AIC = d + k * sum(diag(Delta)), deltabar = deltabar)
  }
  
  aic <- round(extractAIC.svycoxph(model, k = 2)[2], decimal)
  metric.mat <- cbind(c(NA, no.obs, no.event, aic), matrix(NA, 4, ncol(fix.all) - 1))
  rownames(metric.mat) <- c(NA, "No. of observations", "No. of events", "AIC")
  
  ## caption
  surv.string <- as.character(attr(model$terms, "variables")[[2]])
  time.var.name <- surv.string[2]
  status.var.name <-  surv.string[3]
  intro <- paste("Survey cox model on time ('", time.var.name, "') to event ('", status.var.name, "')", sep="")
  
  return(list(table = fix.all.unlist, metric = metric.mat, caption = intro))
  
  
}