R/cox2.R

In jstable: Create Tables from Different Types of Regression

#' @title cox2.display: table for coxph.object with model option: TRUE - allow "frailty" or "cluster" model
#' @description Table for coxph.object with model option: TRUE - allow "frailty" or "cluster" model
#' @param cox.obj.withmodel coxph.object with model option: TRUE
#' @param dec Decimal point, Default: 2
#' @return Table, cluster/frailty info, metrics, caption
#' @details GEE like - cluster, Mixed effect model like - frailty
#' @examples
#' library(survival)
#' data(lung)
#' fit1 <- coxph(Surv(time, status) ~ ph.ecog + age + cluster(inst), data = lung, model = TRUE)
#' fit2 <- coxph(Surv(time, status) ~ ph.ecog + age + frailty(inst), data = lung, model = TRUE)
#' cox2.display(fit1)
#' cox2.display(fit2)
#' @rdname cox2.display
#' @export
#' @importFrom survival coxph cluster frailty
#' @importFrom stats formula update

cox2.display <- function(cox.obj.withmodel, dec = 2) {
  model <- cox.obj.withmodel
  if (!any(class(model) == "coxph")) {
    stop("Model not from Cox model")
  }

  xf <- attr(model$terms, "term.labels") # Independent vars
  xf.old <- xf
  xc <- NULL
  xc.vn <- NULL
  mtype <- "normal"

  if (length(grep("strata", xf)) > 0) {
    xf <- xf[-grep("strata", xf)]
  } else if (length(grep("frailty\\(", xf)) > 0) {
    xf <- xf[-grep("frailty\\(", xf)]
    mtype <- "frailty"
    xc <- setdiff(xf.old, xf)
    xc.vn <- strsplit(strsplit(xc, "frailty\\(")[[1]][2], "\\)")[[1]][1]
  } else if (!(is.null(model$call$cluster))) {
    mtype <- "cluster"
    # xfull <-  strsplit(as.character(model$call[[2]][3]), " \\+ ")[[1]]
    # xc <- setdiff(xfull, xf)
    # xf <- ifelse(length(grep("cluster\\(",xf)) > 0, xf[-grep("cluster\\(",xf)], xf)
    # xc <- setdiff(xf.old, xf)
    xc <- as.character(model$call$cluster)
    xc.vn <- xc
    # xc.vn <- strsplit(strsplit(xc, "cluster\\(")[[1]][2], "\\)")[[1]][1]
  }

  formula.surv <- as.character(model$formula)[2]
  formula.ranef <- paste(" + ", xc, sep = "")
  mdata <- model$model

  if (length(xc) == 0) {
    formula.ranef <- NULL
  } else {
    names(mdata)[names(mdata) == xc] <- xc.vn
  }

  # if (is.null(data)){
  #  mdata = data.frame(get(as.character(model$call)[3]))
  # } else{
  #  mdata = data.frame(data)
  # }



  if (length(xf) == 1) {
    uni.res <- data.frame(summary(model)$coefficients)
    # uni.res <- data.frame(summary(coxph(as.formula(paste("mdata[, 1]", "~", xf, formula.ranef, sep="")), data = mdata))$coefficients)
    rn.uni <- lapply(list(uni.res), rownames)
    names(uni.res)[ncol(uni.res)] <- "p"
    uni.res2 <- NULL
    if (mtype == "normal") {
      uni.res2 <- uni.res[, c(1, 3, 4, 5)]
      if (length(grep("robust.se", names(uni.res))) > 0) {
        uni.res2 <- uni.res[, c(1, 4, 5, 6)]
      }
    } else if (mtype == "cluster") {
      uni.res2 <- uni.res[, c(1, 4, 5, 6)]
    } else {
      uni.res2 <- uni.res[-nrow(uni.res), c(1, 3, 4, 6)]
    }
    fix.all <- coxExp(uni.res2, dec = dec)
    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 {
    mdata2 <- cbind(matrix(sapply(mdata[, 1], `[[`, 1), ncol = 2), mdata[, -1])
    names(mdata2)[1:2] <- as.character(model$formula[[2]][2:3])
    if (!is.null(xc.vn)) {
      names(mdata2)[ncol(mdata2)] <- xc.vn
    }
    basemodel <- update(model, stats::formula(paste(c(". ~ .", xf), collapse = " - ")), data = mdata2)
    unis <- lapply(xf, function(x) {
      newfit <- update(basemodel, stats::formula(paste0(". ~ . +", x)), data = mdata2)
      uni.res <- data.frame(summary(newfit)$coefficients)
      uni.res <- uni.res[grep(x, rownames(uni.res)), ]
      # uni.res <- uni.res[c(2:nrow(uni.res), 1), ]
      # uni.res <- data.frame(summary(coxph(as.formula(paste("mdata[, 1]", "~", x, formula.ranef, sep="")), data = mdata))$coefficients)
      names(uni.res)[ncol(uni.res)] <- "p"
      uni.res2 <- NULL
      if (mtype == "normal") {
        uni.res2 <- uni.res[, c(1, 3, 4, 5)]
      } else if (mtype == "cluster") {
        uni.res2 <- uni.res[, c(1, 4, 5, 6)]
      } else {
        uni.res2 <- uni.res[, c(1, 3, 4, 6)]
      }
      return(uni.res2)
    })
    rn.uni <- lapply(unis, rownames)
    unis2 <- Reduce(rbind, unis)
    uni.res <- unis2
    mul.res <- data.frame(coefNA(model))
    uni.res <- uni.res[rownames(uni.res) %in% rownames(mul.res), ]
    colnames(mul.res)[ncol(mul.res)] <- "p"
    fix.all <- cbind(coxExp(uni.res, dec = dec), coxExp(mul.res[rownames(uni.res), names(uni.res)], dec = dec))
    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(1:length(xf), function(x) {
    fix.all[rownames(fix.all) %in% rn.uni[[x]], ]
  })
  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(1:length(xf), function(x) {
    rownames(fix.all)[rownames(fix.all) %in% rn.uni[[x]]]
  })
  varnum.2fac <- which(lapply(xf, function(x) {
    length(sapply(mdata, levels)[[x]])
  }) == 2)
  lapply(varnum.2fac, function(x) {
    rn.list[[x]] <<- paste(xf[x], ": ", levels(mdata[, xf[x]])[2], " vs ", levels(mdata[, xf[x]])[1], sep = "")
  })
  lapply(varnum.mfac, function(x) {
    rn.list[[x]] <<- c(paste(xf[x], ": ref.=", levels(mdata[, 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]), dec + 1))
  }


  ## random effect
  # ranef = unlist(model$vcoef)
  # ranef.out = round(ranef, dec)
  ranef.mat <- NULL
  if (mtype == "cluster") {
    ranef.mat <- cbind(c(NA, NA), matrix(NA, length(xc) + 1, ncol(fix.all) - 1))
    # clname = strsplit(xc, "\\(")[[1]]
    clname <- c("cluster", xc)
    cvname <- strsplit(paste(clname[-1], collapse = "("), "\\)")[[1]]
    cvname <- paste(cvname[length(cvname)], collapse = ")")
    rownames(ranef.mat) <- c(clname[1], cvname)
  } else if (mtype == "frailty") {
    ranef.mat <- cbind(c(NA, NA), matrix(NA, length(xc) + 1, ncol(fix.all) - 1))
    clname <- strsplit(xc, "\\(")[[1]]
    cvname <- strsplit(paste(clname[-1], collapse = "("), "\\)")[[1]]
    cvname <- paste(cvname[length(cvname)], collapse = ")")
    rownames(ranef.mat) <- c(clname[1], cvname)
  }


  ## metric
  # no.grp = unlist(lapply(model$frail, length))
  no.obs <- model$n
  no.event <- model$nevent
  metric.mat <- cbind(c(NA, no.obs, no.event), matrix(NA, 3, ncol(fix.all) - 1))
  rownames(metric.mat) <- c(NA, "No. of observations", "No. of events")

  ## Integrated ll
  # ll = model$loglik[2]
  # aic = -2 * ll -2*model$df[1]

  ## caption
  surv.string <- as.character(attr(model$terms, "variables")[[2]])
  time.var.name <- surv.string[2]
  status.var.name <- surv.string[3]
  intro <- paste("Cox model on time ('", time.var.name, "') to event ('", status.var.name, "')", sep = "")
  if (mtype == "cluster") {
    intro <- paste("Marginal", intro, "- Group", cvname)
  } else if (mtype == "frailty") {
    intro <- paste("Frailty", intro, "- Group", cvname)
  }

  var.names0 <- attr(model$terms, "term.labels")
  if (length(grep("strata", var.names0)) > 0) {
    intro <- paste(intro, " with '", var.names0[grep("strata", var.names0)], "'", sep = "")
  }

  if (is.null(ranef.mat)) {
    return(list(table = fix.all.unlist, metric = metric.mat, caption = intro))
  } else {
    return(list(table = fix.all.unlist, ranef = ranef.mat, metric = metric.mat, caption = intro))
  }
}