Commit ⋅ jinseob2kim/jsmodule

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NAMESPACE has changed.

NEWS.md has changed.

man/timeROChelper.Rd has changed.

man/timeROC_table.Rd has changed.

@@ -66,8 +66,7 @@

#' @param data data
#' @param design.survey survey data, Default: NULL
#' @param id.cluster cluster variable if marginal model, Default: NULL
#' @param iid logical. if calculationg confidence interval, Default: T
#' @return timeROC object
#' @return timeROC and coxph object
#' @details Helper function for timerocModule
#' @examples
#' #library(survival)

@@ -85,7 +84,7 @@




timeROChelper <- function(var.event, var.time, vars.ind, t, data, design.survey = NULL, id.cluster = NULL, iid = T) {
timeROChelper <- function(var.event, var.time, vars.ind, t, data, design.survey = NULL, id.cluster = NULL) {
  data[[var.event]] <- as.numeric(as.vector(data[[var.event]]))
  forms <- as.formula(paste0("survival::Surv(", var.time, ",", var.event, ") ~ " , paste(vars.ind, collapse = "+")))


@@ -100,6 +99,7 @@

  } else{
    cmodel <- survey::svycoxph(forms, design = design.survey, y = T)
  }

  lp <- stats::predict(cmodel, type = "lp")
  vec.y <- sapply(cmodel$y, `[[`, 1)
  out <- timeROC::timeROC(T = vec.y[1:(length(vec.y)/2)],

@@ -107,22 +107,35 @@

                          marker = lp,
                          cause = 1,
                          weighting="marginal",
                          times = t,
                          iid = iid)
                          times = t)

  ## Coxph object
  data[[var.event]][data[[var.event]] == 1 & data[[var.time]] > t] <- 0
  data[[var.time]][data[[var.time]] > t] <- t
  if (is.null(design.survey)){
    if (!is.null(id.cluster)){
      cmodel <- survival::coxph(forms, data = data, y = T, cluster = get(id.cluster))
    } else{
      cmodel <- survival::coxph(forms, data = data, y = T)
    }

  return(out)
  } else{
    cmodel <- survey::svycoxph(forms, design = design.survey, y = T)
  }

  return(list(coxph = cmodel, timeROC = out))
}




#' @title timeROC_table: extract AUC information from list of timeROC object.
#' @description extract AUC information from list of timeROC object.
#' @param ListModel list of timeROC object
#' @title timeROC_table: extract AUC information from list of timeROChelper object.
#' @description extract AUC information from list of timeROChelper object.
#' @param ListModel list of timeROChelper object
#' @param dec.auc digits for AUC, Default: 3
#' @param dec.p digits for p value, Default: 3
#' @return table of AUC information
#' @details extract AUC information from list of timeROC object.
#' @details extract AUC information from list of timeROChelper object.
#' @examples
#' #library(survival)
#' #list.timeROC <- lapply(list("age", c("age", "sex")),

@@ -134,31 +147,33 @@

#'  \code{\link[stats]{confint}}
#'  \code{\link[data.table]{data.table}}
#' @rdname timeROC_table
#' @importFrom stats confint
#' @importFrom stats confint qnorm
#' @importFrom data.table data.table
#' @importFrom survival concordance

timeROC_table <- function(ListModel, dec.auc =3, dec.p = 3){
  auc <- round(sapply(ListModel, function(x){x$AUC[[2]]}), dec.auc)
  if (all(sapply(ListModel, `[[`, "iid"))){
    auc.ci <- sapply(ListModel, function(x){ifelse(is.na(x$AUC[[2]]), NA, paste(round(stats::confint(x)$CI_AUC/100, dec.auc), collapse = "-"))})

    if (length(ListModel) == 1){
      out <- data.table::data.table(paste0("Model ", seq_along(ListModel)), auc, auc.ci)
      names(out) <- c("Prediction Model", "AUC", "95% CI")
    } else{
      auc.pdiff <- c(NA, sapply(seq_along(ListModel)[-1],
                                function(x){
                                  p <- timeROC::compare(ListModel[[x]], ListModel[[x-1]])$p_values_AUC[2]
                                  p <- ifelse(p < 0.001, "< 0.001", round(p, dec.p))
                                  return(p)
                                }))

      out <- data.table::data.table(paste0("Model ", seq_along(ListModel)), auc, auc.ci, auc.pdiff)
      names(out) <- c("Prediction Model", "AUC", "95% CI", "P-value for AUC Difference")
    }
  res.roc <- eval(parse(text = paste0("survival::concordance(", paste(paste0("lapply(ListModel, `[[`, 'coxph')[[", seq_along(ListModel), "]]"), collapse = ", "), ")")))
  auc <- res.roc$concordance
  se1.96 <- stats::qnorm(0.975) * sqrt(ifelse(length(ListModel) == 1, res.roc$var, diag(res.roc$var)))
  auc.ci <- paste0(round(auc - se1.96, dec.auc), "-", round(auc + se1.96, dec.auc))
  auc <- round(auc, dec.auc)

  if (length(ListModel) == 1){
    out <- data.table::data.table(paste0("Model ", seq_along(ListModel)), auc, auc.ci)
    names(out) <- c("Prediction Model", "AUC", "95% CI")
  } else{
    out <- data.table::data.table(paste0("Model ", seq_along(ListModel)), auc)
    names(out) <- c("Prediction Model", "AUC")
    auc.pdiff <- c(NA, sapply(seq_along(ListModel)[-1],
                              function(x){
                                contr <- c(-1, 1)
                                dtest <- contr %*% res.roc$concordance[(x-1):x]
                                dvar <- contr %*% res.roc$var[(x-1):x, (x-1):x] %*% contr
                                p <- 2 * pnorm(abs(dtest/sqrt(dvar)), lower.tail = F)
                                p <- ifelse(p < 0.001, "< 0.001", round(p, dec.p))
                                return(p)
                              }))

    out <- data.table::data.table(paste0("Model ", seq_along(ListModel)), auc, auc.ci, auc.pdiff)
    names(out) <- c("Prediction Model", "AUC", "95% CI", "P-value for AUC Difference")
  }



@@ -299,7 +314,7 @@

timerocModule <- function(input, output, session, data, data_label, data_varStruct = NULL, nfactor.limit = 10, design.survey = NULL, id.cluster = NULL, iid = T, NRIIDI = T) {

  ## To remove NOTE.
  compare <- level <- variable <- FP <- TP <- model <- NULL
  ListModel <- compare <- level <- variable <- FP <- TP <- model <- NULL

  if (is.null(data_varStruct)){
    data_varStruct <- reactive(list(variable = names(data())))

@@ -549,7 +564,7 @@


    if (is.null(design.survey)){
      if (is.null(id.cluster)){
        res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind =  x, t = input$time_to_roc, data = data.km, iid = iid)})
        res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind =  x, t = input$time_to_roc, data = data.km)})

        if ((nmodel() == 1 | NRIIDI == F)){
          res.tb <- timeROC_table(res.roc)

@@ -564,7 +579,7 @@



      } else{
        res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind =  x, t = input$time_to_roc, data = data.km, id.cluster = id.cluster(), iid = iid)})
        res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind =  x, t = input$time_to_roc, data = data.km, id.cluster = id.cluster())})

        if (nmodel() == 1 | NRIIDI == F){
          res.tb <- timeROC_table(res.roc)

@@ -612,7 +627,7 @@


      }
      res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind =  x,
                                                            t = input$time_to_roc, data = data.km, design.survey = data.design, iid = iid)})
                                                            t = input$time_to_roc, data = data.km, design.survey = data.design)})

      if (nmodel() == 1 | NRIIDI == F){
        res.tb <- timeROC_table(res.roc)

@@ -626,11 +641,12 @@

      }
    }

    res.timeROC <- lapply(res.roc, `[[`, "timeROC")
    data.rocplot <- data.table::rbindlist(
      lapply(1:length(res.roc),
      lapply(1:length(res.timeROC),
             function(x){
               data.table::data.table(FP = res.roc[[x]]$FP[, which(res.roc[[x]]$times == input$time_to_roc)],
                                      TP = res.roc[[x]]$TP[, which(res.roc[[x]]$times == input$time_to_roc)],
               data.table::data.table(FP = res.timeROC[[x]]$FP[, which(res.timeROC[[x]]$times == input$time_to_roc)],
                                      TP = res.timeROC[[x]]$TP[, which(res.timeROC[[x]]$times == input$time_to_roc)],
                                      model = paste0("model ", x))
               }))


@@ -772,7 +788,7 @@

timerocModule2 <- function(input, output, session, data, data_label, data_varStruct = NULL, nfactor.limit = 10, design.survey = NULL, id.cluster = NULL, iid = T, NRIIDI = T) {

  ## To remove NOTE.
  compare <- level <- variable <- FP <- TP <- model <- NULL
  ListModel <- compare <- level <- variable <- FP <- TP <- model <- NULL

  if (is.null(data_varStruct)){
    data_varStruct <- reactive(list(variable = names(data())))

@@ -1002,7 +1018,7 @@


    if (is.null(design.survey)){
      if (is.null(id.cluster)){
        res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind =  x, t = input$time_to_roc, data = data.km, iid = iid)})
        res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind =  x, t = input$time_to_roc, data = data.km)})

        if (nmodel() == 1 | NRIIDI == F){
          res.tb <- timeROC_table(res.roc)

@@ -1017,7 +1033,7 @@



      } else{
        res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind =  x, t = input$time_to_roc, data = data.km, id.cluster = id.cluster(), iid = iid)})
        res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind =  x, t = input$time_to_roc, data = data.km, id.cluster = id.cluster())})

        if (nmodel() == 1 | NRIIDI == F){
          res.tb <- timeROC_table(res.roc)

@@ -1065,7 +1081,7 @@


      }
      res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind =  x,
                                                            t = input$time_to_roc, data = data.km, design.survey = data.design, iid = iid)})
                                                            t = input$time_to_roc, data = data.km, design.survey = data.design)})

      if (nmodel() == 1 | NRIIDI == F){
        res.tb <- timeROC_table(res.roc)

@@ -1079,11 +1095,12 @@

      }
    }

    res.timeROC <- lapply(res.roc, `[[`, "timeROC")
    data.rocplot <- data.table::rbindlist(
      lapply(1:length(res.roc),
      lapply(1:length(res.timeROC),
             function(x){
               data.table::data.table(FP = res.roc[[x]]$FP[, which(res.roc[[x]]$times == input$time_to_roc)],
                                      TP = res.roc[[x]]$TP[, which(res.roc[[x]]$times == input$time_to_roc)],
               data.table::data.table(FP = res.timeROC[[x]]$FP[, which(res.timeROC[[x]]$times == input$time_to_roc)],
                                      TP = res.timeROC[[x]]$TP[, which(res.timeROC[[x]]$times == input$time_to_roc)],
                                      model = paste0("model ", x))
             }))


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107	107		marker = lp,
108	108		cause = 1,
109	109		weighting="marginal",
110		-	times = t,
111		-	iid = iid)
	110	+	times = t)
	111	+
	112	+	## Coxph object
	113	+	data[[var.event]][data[[var.event]] == 1 & data[[var.time]] > t] <- 0
	114	+	data[[var.time]][data[[var.time]] > t] <- t
	115	+	if (is.null(design.survey)){
	116	+	if (!is.null(id.cluster)){
	117	+	cmodel <- survival::coxph(forms, data = data, y = T, cluster = get(id.cluster))
	118	+	} else{
	119	+	cmodel <- survival::coxph(forms, data = data, y = T)
	120	+	}
112	121
113		-	return(out)
	122	+	} else{
	123	+	cmodel <- survey::svycoxph(forms, design = design.survey, y = T)
	124	+	}
	125	+
	126	+	return(list(coxph = cmodel, timeROC = out))
114	127		}
115	128
116	129
117	130
118	131
119		-	#' @title timeROC_table: extract AUC information from list of timeROC object.
120		-	#' @description extract AUC information from list of timeROC object.
121		-	#' @param ListModel list of timeROC object
	132	+	#' @title timeROC_table: extract AUC information from list of timeROChelper object.
	133	+	#' @description extract AUC information from list of timeROChelper object.
	134	+	#' @param ListModel list of timeROChelper object
122	135		#' @param dec.auc digits for AUC, Default: 3
123	136		#' @param dec.p digits for p value, Default: 3
124	137		#' @return table of AUC information
125		-	#' @details extract AUC information from list of timeROC object.
	138	+	#' @details extract AUC information from list of timeROChelper object.
126	139		#' @examples
127	140		#' #library(survival)
128	141		#' #list.timeROC <- lapply(list("age", c("age", "sex")),

134	147		#' \code{\link[stats]{confint}}
135	148		#' \code{\link[data.table]{data.table}}
136	149		#' @rdname timeROC_table
137		-	#' @importFrom stats confint
	150	+	#' @importFrom stats confint qnorm
138	151		#' @importFrom data.table data.table
	152	+	#' @importFrom survival concordance
139	153
140	154		timeROC_table <- function(ListModel, dec.auc =3, dec.p = 3){
141		-	auc <- round(sapply(ListModel, function(x){x$AUC[[2]]}), dec.auc)
142		-	if (all(sapply(ListModel, `[[`, "iid"))){
143		-	auc.ci <- sapply(ListModel, function(x){ifelse(is.na(x$AUC[[2]]), NA, paste(round(stats::confint(x)$CI_AUC/100, dec.auc), collapse = "-"))})
144		-
145		-	if (length(ListModel) == 1){
146		-	out <- data.table::data.table(paste0("Model ", seq_along(ListModel)), auc, auc.ci)
147		-	names(out) <- c("Prediction Model", "AUC", "95% CI")
148		-	} else{
149		-	auc.pdiff <- c(NA, sapply(seq_along(ListModel)[-1],
150		-	function(x){
151		-	p <- timeROC::compare(ListModel[[x]], ListModel[[x-1]])$p_values_AUC[2]
152		-	p <- ifelse(p < 0.001, "< 0.001", round(p, dec.p))
153		-	return(p)
154		-	}))
155		-
156		-	out <- data.table::data.table(paste0("Model ", seq_along(ListModel)), auc, auc.ci, auc.pdiff)
157		-	names(out) <- c("Prediction Model", "AUC", "95% CI", "P-value for AUC Difference")
158		-	}
	155	+	res.roc <- eval(parse(text = paste0("survival::concordance(", paste(paste0("lapply(ListModel, `[[`, 'coxph')[[", seq_along(ListModel), "]]"), collapse = ", "), ")")))
	156	+	auc <- res.roc$concordance
	157	+	se1.96 <- stats::qnorm(0.975) * sqrt(ifelse(length(ListModel) == 1, res.roc$var, diag(res.roc$var)))
	158	+	auc.ci <- paste0(round(auc - se1.96, dec.auc), "-", round(auc + se1.96, dec.auc))
	159	+	auc <- round(auc, dec.auc)
	160	+
	161	+	if (length(ListModel) == 1){
	162	+	out <- data.table::data.table(paste0("Model ", seq_along(ListModel)), auc, auc.ci)
	163	+	names(out) <- c("Prediction Model", "AUC", "95% CI")
159	164		} else{
160		-	out <- data.table::data.table(paste0("Model ", seq_along(ListModel)), auc)
161		-	names(out) <- c("Prediction Model", "AUC")
	165	+	auc.pdiff <- c(NA, sapply(seq_along(ListModel)[-1],
	166	+	function(x){
	167	+	contr <- c(-1, 1)
	168	+	dtest <- contr %*% res.roc$concordance[(x-1):x]
	169	+	dvar <- contr %% res.roc$var[(x-1):x, (x-1):x] %% contr
	170	+	p <- 2 * pnorm(abs(dtest/sqrt(dvar)), lower.tail = F)
	171	+	p <- ifelse(p < 0.001, "< 0.001", round(p, dec.p))
	172	+	return(p)
	173	+	}))
	174	+
	175	+	out <- data.table::data.table(paste0("Model ", seq_along(ListModel)), auc, auc.ci, auc.pdiff)
	176	+	names(out) <- c("Prediction Model", "AUC", "95% CI", "P-value for AUC Difference")
162	177		}
163	178
164	179

299	314		timerocModule <- function(input, output, session, data, data_label, data_varStruct = NULL, nfactor.limit = 10, design.survey = NULL, id.cluster = NULL, iid = T, NRIIDI = T) {
300	315
301	316		## To remove NOTE.
302		-	compare <- level <- variable <- FP <- TP <- model <- NULL
	317	+	ListModel <- compare <- level <- variable <- FP <- TP <- model <- NULL
303	318
304	319		if (is.null(data_varStruct)){
305	320		data_varStruct <- reactive(list(variable = names(data())))

549	564
550	565		if (is.null(design.survey)){
551	566		if (is.null(id.cluster)){
552		-	res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind = x, t = input$time_to_roc, data = data.km, iid = iid)})
	567	+	res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind = x, t = input$time_to_roc, data = data.km)})
553	568
554	569		if ((nmodel() == 1 \| NRIIDI == F)){
555	570		res.tb <- timeROC_table(res.roc)

564	579
565	580
566	581		} else{
567		-	res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind = x, t = input$time_to_roc, data = data.km, id.cluster = id.cluster(), iid = iid)})
	582	+	res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind = x, t = input$time_to_roc, data = data.km, id.cluster = id.cluster())})
568	583
569	584		if (nmodel() == 1 \| NRIIDI == F){
570	585		res.tb <- timeROC_table(res.roc)

66	66		#' @param data data
67	67		#' @param design.survey survey data, Default: NULL
68	68		#' @param id.cluster cluster variable if marginal model, Default: NULL
69		-	#' @param iid logical. if calculationg confidence interval, Default: T
70		-	#' @return timeROC object
	69	+	#' @return timeROC and coxph object
71	70		#' @details Helper function for timerocModule
72	71		#' @examples
73	72		#' #library(survival)

85	84
86	85
87	86
88		-	timeROChelper <- function(var.event, var.time, vars.ind, t, data, design.survey = NULL, id.cluster = NULL, iid = T) {
	87	+	timeROChelper <- function(var.event, var.time, vars.ind, t, data, design.survey = NULL, id.cluster = NULL) {
89	88		data[[var.event]] <- as.numeric(as.vector(data[[var.event]]))
90	89		forms <- as.formula(paste0("survival::Surv(", var.time, ",", var.event, ") ~ " , paste(vars.ind, collapse = "+")))
91	90

100	99		} else{
101	100		cmodel <- survey::svycoxph(forms, design = design.survey, y = T)
102	101		}
	102	+
103	103		lp <- stats::predict(cmodel, type = "lp")
104	104		vec.y <- sapply(cmodel$y, `[[`, 1)
105	105		out <- timeROC::timeROC(T = vec.y[1:(length(vec.y)/2)],

612	627
613	628		}
614	629		res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind = x,
615		-	t = input$time_to_roc, data = data.km, design.survey = data.design, iid = iid)})
	630	+	t = input$time_to_roc, data = data.km, design.survey = data.design)})
616	631
617	632		if (nmodel() == 1 \| NRIIDI == F){
618	633		res.tb <- timeROC_table(res.roc)

626	641		}
627	642		}
628	643
	644	+	res.timeROC <- lapply(res.roc, `[[`, "timeROC")
629	645		data.rocplot <- data.table::rbindlist(
630		-	lapply(1:length(res.roc),
	646	+	lapply(1:length(res.timeROC),
631	647		function(x){
632		-	data.table::data.table(FP = res.roc[[x]]$FP[, which(res.roc[[x]]$times == input$time_to_roc)],
633		-	TP = res.roc[[x]]$TP[, which(res.roc[[x]]$times == input$time_to_roc)],
	648	+	data.table::data.table(FP = res.timeROC[[x]]$FP[, which(res.timeROC[[x]]$times == input$time_to_roc)],
	649	+	TP = res.timeROC[[x]]$TP[, which(res.timeROC[[x]]$times == input$time_to_roc)],
634	650		model = paste0("model ", x))
635	651		}))
636	652

772	788		timerocModule2 <- function(input, output, session, data, data_label, data_varStruct = NULL, nfactor.limit = 10, design.survey = NULL, id.cluster = NULL, iid = T, NRIIDI = T) {
773	789
774	790		## To remove NOTE.
775		-	compare <- level <- variable <- FP <- TP <- model <- NULL
	791	+	ListModel <- compare <- level <- variable <- FP <- TP <- model <- NULL
776	792
777	793		if (is.null(data_varStruct)){
778	794		data_varStruct <- reactive(list(variable = names(data())))

1002	1018
1003	1019		if (is.null(design.survey)){
1004	1020		if (is.null(id.cluster)){
1005		-	res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind = x, t = input$time_to_roc, data = data.km, iid = iid)})
	1021	+	res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind = x, t = input$time_to_roc, data = data.km)})
1006	1022
1007	1023		if (nmodel() == 1 \| NRIIDI == F){
1008	1024		res.tb <- timeROC_table(res.roc)

1017	1033
1018	1034
1019	1035		} else{
1020		-	res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind = x, t = input$time_to_roc, data = data.km, id.cluster = id.cluster(), iid = iid)})
	1036	+	res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind = x, t = input$time_to_roc, data = data.km, id.cluster = id.cluster())})
1021	1037
1022	1038		if (nmodel() == 1 \| NRIIDI == F){
1023	1039		res.tb <- timeROC_table(res.roc)

1065	1081
1066	1082		}
1067	1083		res.roc <- lapply(indeps(), function(x){timeROChelper(input$event_km, input$time_km, vars.ind = x,
1068		-	t = input$time_to_roc, data = data.km, design.survey = data.design, iid = iid)})
	1084	+	t = input$time_to_roc, data = data.km, design.survey = data.design)})
1069	1085
1070	1086		if (nmodel() == 1 \| NRIIDI == F){
1071	1087		res.tb <- timeROC_table(res.roc)

1079	1095		}
1080	1096		}
1081	1097
	1098	+	res.timeROC <- lapply(res.roc, `[[`, "timeROC")
1082	1099		data.rocplot <- data.table::rbindlist(
1083		-	lapply(1:length(res.roc),
	1100	+	lapply(1:length(res.timeROC),
1084	1101		function(x){
1085		-	data.table::data.table(FP = res.roc[[x]]$FP[, which(res.roc[[x]]$times == input$time_to_roc)],
1086		-	TP = res.roc[[x]]$TP[, which(res.roc[[x]]$times == input$time_to_roc)],
	1102	+	data.table::data.table(FP = res.timeROC[[x]]$FP[, which(res.timeROC[[x]]$times == input$time_to_roc)],
	1103	+	TP = res.timeROC[[x]]$TP[, which(res.timeROC[[x]]$times == input$time_to_roc)],
1087	1104		model = paste0("model ", x))
1088	1105		}))
1089	1106

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