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#' @title coxUI: shiny modulde UI for Cox's model.
#' @description Shiny modulde UI for Cox's model.
#' @param id id
#' @return coxUI
#' @details Shiny modulde UI for Cox's model.
#' @examples
#' coxUI(1)
#' @rdname coxUI
#' @export
coxUI <- function(id) {
# Create a namespace function using the provided id
ns <- NS(id)
tagList(
uiOutput(ns("eventtime")),
checkboxInput(ns("check_rangetime"), "Choose time ranges"),
uiOutput(ns("rangetime")),
uiOutput(ns("indep")),
sliderInput(ns("decimal"), "Digits",
min = 1, max = 4, value = 2
),
checkboxInput(ns("subcheck"), "Sub-group analysis"),
uiOutput(ns("subvar")),
uiOutput(ns("subval")),
checkboxInput(ns("step_check"), "Stepwise variable selection"),
uiOutput(ns("step_direction")),
uiOutput(ns("step_scope"))
)
}
#' @title coxModule: shiny modulde server for Cox's model.
#' @description Shiny modulde server for Cox's model.
#' @param input input
#' @param output output
#' @param session session
#' @param data reactive data
#' @param data_label reactuve data label
#' @param data_varStruct reactive list of variable structure, Default: NULL
#' @param nfactor.limit nlevels limit in factor variable, Default: 10
#' @param design.survey reactive survey data. default: NULL
#' @param default.unires Set default independent variables using univariate analysis.
#' @param limit.unires Change to default.unires = F if number of independent variables > limit.unires, Default: 20
#' @param id.cluster reactive cluster variable if marginal cox model, Default: NULL
#' @param ties.coxph 'coxph' ties option, one of 'efron', 'breslow', 'exact', default: 'erfon'
#' @return Shiny modulde server for Cox's model.
#' @details Shiny modulde server for Cox's model.
#' @examples
#' library(shiny)
#' library(DT)
#' library(data.table)
#' library(jstable)
#' ui <- fluidPage(
#' sidebarLayout(
#' sidebarPanel(
#' coxUI("cox")
#' ),
#' mainPanel(
#' DTOutput("coxtable")
#' )
#' )
#' )
#'
#' server <- function(input, output, session) {
#' data <- reactive(mtcars)
#' data.label <- reactive(jstable::mk.lev(mtcars))
#'
#' out_cox <- callModule(coxModule, "cox",
#' data = data, data_label = data.label,
#' data_varStruct = NULL
#' )
#'
#' output$coxtable <- renderDT({
#' datatable(out_cox()$table, rownames = T, caption = out_cox()$caption)
#' })
#' }
#' @rdname coxModule
#' @export
#' @import shiny
#' @importFrom data.table data.table .SD :=
#' @importFrom labelled var_label<-
#' @importFrom stats glm as.formula model.frame step
#' @importFrom purrr map_lgl
#' @importFrom survival cluster coxph Surv
coxModule <- function(input, output, session, data, data_label, data_varStruct = NULL, nfactor.limit = 10, design.survey = NULL, default.unires = T, limit.unires = 20, id.cluster = NULL, ties.coxph = "efron") {
## To remove NOTE.
data.cox.step <- level <- val_label <- variable <- NULL
if (is.null(data_varStruct)) {
data_varStruct <- reactive(list(variable = names(data())))
}
vlist <- reactive({
mklist <- function(varlist, vars) {
lapply(
varlist,
function(x) {
inter <- intersect(x, vars)
if (length(inter) == 1) {
inter <- c(inter, "")
}
return(inter)
}
)
}
factor_vars <- names(data())[data()[, lapply(.SD, class) %in% c("factor", "character")]]
# factor_vars <- names(data())[sapply(names(data()), function(x){class(data()[[x]]) %in% c("factor", "character")})]
factor_list <- mklist(data_varStruct(), factor_vars)
conti_vars <- setdiff(names(data()), factor_vars)
if (!is.null(design.survey)) {
conti_vars <- setdiff(conti_vars, c(names(design.survey()$allprob), names(design.survey()$strata), names(design.survey()$cluster)))
}
conti_vars_positive <- conti_vars[unlist(data()[, lapply(.SD, function(x) {
min(x, na.rm = T) >= 0
}), .SDcols = conti_vars])]
conti_list <- mklist(data_varStruct(), conti_vars)
nclass_factor <- unlist(data()[, lapply(.SD, function(x) {
length(levels(x))
}), .SDcols = factor_vars])
# nclass_factor <- sapply(factor_vars, function(x){length(unique(data()[[x]]))})
class01_factor <- unlist(data()[, lapply(.SD, function(x) {
identical(levels(x), c("0", "1"))
}), .SDcols = factor_vars])
validate(
need(length(class01_factor) >= 1, "No categorical variables coded as 0, 1 in data")
)
factor_01vars <- factor_vars[class01_factor]
factor_01_list <- mklist(data_varStruct(), factor_01vars)
group_vars <- factor_vars[nclass_factor >= 2 & nclass_factor <= nfactor.limit & nclass_factor < nrow(data())]
group_list <- mklist(data_varStruct(), group_vars)
except_vars <- factor_vars[nclass_factor > nfactor.limit | nclass_factor == 1 | nclass_factor == nrow(data())]
return(list(
factor_vars = factor_vars, factor_list = factor_list, conti_vars = conti_vars, conti_list = conti_list, conti_vars_positive = conti_vars_positive,
factor_01vars = factor_01vars, factor_01_list = factor_01_list, group_vars = group_vars, group_list = group_list, except_vars = except_vars
))
})
output$eventtime <- renderUI({
validate(
need(length(vlist()$factor_01vars) >= 1, "No candidate event variables coded as 0, 1"),
need(length(vlist()$conti_vars_positive) >= 1, "No candidate time variables")
)
tagList(
selectInput(session$ns("event_cox"), "Event",
choices = mklist(data_varStruct(), vlist()$factor_01vars), multiple = F,
selected = NULL
),
selectInput(session$ns("time_cox"), "Time",
choices = mklist(data_varStruct(), vlist()$conti_vars_positive), multiple = F,
selected = NULL
)
)
})
observeEvent(input$check_rangetime, {
output$rangetime <- renderUI({
req(input$check_rangetime == T)
sliderInput(session$ns("range_time"), "Time ranges",
min = min(data()[[input$time_cox]], na.rm = T), max = max(data()[[input$time_cox]], na.rm = T),
value = c(min(data()[[input$time_cox]], na.rm = T), median(data()[[input$time_cox]], na.rm = T))
)
})
})
output$indep <- renderUI({
req(!is.null(input$event_cox))
req(!is.null(input$time_cox))
mklist <- function(varlist, vars) {
lapply(
varlist,
function(x) {
inter <- intersect(x, vars)
if (length(inter) == 1) {
inter <- c(inter, "")
}
return(inter)
}
)
}
if (is.null(design.survey)) {
indep.cox <- setdiff(names(data()), c(vlist()$except_vars, input$event_cox, input$time_cox))
if (!is.null(id.cluster)) {
indep.cox <- setdiff(names(data()), c(vlist()$except_vars, input$event_cox, input$time_cox, id.cluster()))
}
if (default.unires) {
data.cox <- data()
if (input$check_rangetime == T) {
data.cox <- data.cox[!(get(input$time_cox) < input$range_time[1])]
data.cox[[input$event_cox]] <- ifelse(data.cox[[input$time_cox]] >= input$range_time[2] & data.cox[[input$event_cox]] == "1", 0, as.numeric(as.vector(data.cox[[input$event_cox]])))
data.cox[[input$time_cox]] <- ifelse(data.cox[[input$time_cox]] >= input$range_time[2], input$range_time[2], data.cox[[input$time_cox]])
}
data.cox[[input$event_cox]] <- as.numeric(as.vector(data.cox[[input$event_cox]]))
varsIni <- sapply(
indep.cox,
function(v) {
if (is.null(id.cluster)) {
forms <- as.formula(paste("survival::Surv(", input$time_cox, ",", input$event_cox, ") ~ ", v, sep = ""))
coef <- tryCatch(summary(survival::coxph(forms, data = data.cox, ties = ties.coxph))$coefficients, error = function(e) {
return(NULL)
})
} else {
forms <- as.formula(paste("survival::Surv(", input$time_cox, ",", input$event_cox, ") ~ ", v, " + cluster(", id.cluster(), ")", sep = ""))
coef <- tryCatch(summary(survival::coxph(forms, data = data.cox, robust = T, ties = ties.coxph))$coefficients, error = function(e) {
return(NULL)
})
}
sigOK <- ifelse(is.null(coef), F, !all(coef[, "Pr(>|z|)"] > 0.05))
return(sigOK)
}
)
if (length(varsIni[varsIni == T]) > limit.unires) {
varsIni <- c(T, rep(F, length(indep.cox) - 1))
}
} else {
varsIni <- c(T, rep(F, length(indep.cox) - 1))
}
} else {
indep.cox <- setdiff(names(data()), c(vlist()$except_vars, input$event_cox, input$time_cox, names(design.survey()$allprob), names(design.survey()$strata), names(design.survey()$cluster)))
if (default.unires) {
data.design <- design.survey()
if (input$check_rangetime == T) {
data.design <- subset(data.design, !(get(input$time_cox) < input$range_time[1]))
data.design$variables[[input$event_cox]] <- ifelse(data.design$variables[[input$time_cox]] >= input$range_time[2] & data.design$variables[[input$event_cox]] == "1", 0, as.numeric(as.vector(data.design$variables[[input$event_cox]])))
data.design$variables[[input$time_cox]] <- ifelse(data.design$variables[[input$time_cox]] >= input$range_time[2], input$range_time[2], data.design$variables[[input$time_cox]])
}
data.design$variables[[input$event_cox]] <- as.numeric(as.vector(data.design$variables[[input$event_cox]]))
varsIni <- sapply(
indep.cox,
function(v) {
forms <- as.formula(paste("survival::Surv(", input$time_cox, ",", input$event_cox, ") ~ ", v, sep = ""))
coef <- tryCatch(summary(survey::svycoxph(forms, design = data.design))$coefficients, error = function(e) {
return(NULL)
})
sigOK <- ifelse(is.null(coef), F, !all(coef[, "Pr(>|z|)"] > 0.05))
return(sigOK)
}
)
if (length(varsIni[varsIni == T]) > limit.unires) {
varsIni <- c(T, rep(F, length(indep.cox) - 1))
}
} else {
varsIni <- c(T, rep(F, length(indep.cox) - 1))
}
}
tagList(
selectInput(session$ns("indep_cox"), "Independent variables",
choices = mklist(data_varStruct(), indep.cox), multiple = T,
selected = indep.cox[varsIni]
)
)
})
observeEvent(input$subcheck, {
output$subvar <- renderUI({
req(input$subcheck == T)
var_subgroup <- setdiff(names(data()), c(input$time_cox, input$event_cox, input$indep_cox))
if (!is.null(id.cluster)) {
var_subgroup <- setdiff(names(data()), c(input$time_cox, input$event_cox, input$indep_cox, id.cluster()))
} else if (!is.null(design.survey)) {
var_subgroup <- setdiff(names(data()), union(c(names(design.survey()$strata), names(design.survey()$cluster), names(design.survey()$allprob)), c(input$time_cox, input$event_cox, input$indep_cox)))
}
var_subgroup_list <- mklist(data_varStruct(), var_subgroup)
validate(
need(length(var_subgroup) > 0, "No variables for sub-group analysis")
)
tagList(
selectInput(session$ns("subvar_cox"), "Sub-group variables",
choices = var_subgroup_list, multiple = T,
selected = var_subgroup[1]
)
)
})
})
output$subval <- renderUI({
req(input$subcheck == T)
req(length(input$subvar_cox) > 0)
outUI <- tagList()
for (v in seq_along(input$subvar_cox)) {
if (input$subvar_cox[[v]] %in% vlist()$factor_vars) {
outUI[[v]] <- selectInput(session$ns(paste0("subval_cox", v)), paste0("Sub-group value: ", input$subvar_cox[[v]]),
choices = data_label()[variable == input$subvar_cox[[v]], level], multiple = T,
selected = data_label()[variable == input$subvar_cox[[v]], level][1]
)
} else {
val <- stats::quantile(data()[[input$subvar_cox[[v]]]], na.rm = T)
outUI[[v]] <- sliderInput(session$ns(paste0("subval_cox", v)), paste0("Sub-group range: ", input$subvar_cox[[v]]),
min = val[1], max = val[5],
value = c(val[2], val[4])
)
}
}
outUI
})
observeEvent(input$step_check, {
output$step_direction <- renderUI({
req(input$step_check == T)
radioButtons(session$ns("step_direction"), "Step direction", choices = c("backward", "forward", "both"), selected = "backward", inline = T)
})
output$step_scope <- renderUI({
req(input$step_check == T)
req(input$indep_cox)
tagList(
fluidRow(
column(6, selectInput(session$ns("step_lower"), "Lower limit", choices = input$indep_cox, selected = NULL, multiple = T)),
column(6, selectInput(session$ns("step_upper"), "Upper limit", choices = input$indep_cox, selected = input$indep_cox, multiple = T))
)
)
})
})
form.cox <- reactive({
validate(
need(!is.null(input$indep_cox), "Please select at least 1 independent variable.")
)
if (is.null(id.cluster)) {
return(as.formula(paste("survival::Surv(", input$time_cox, ",", input$event_cox, ") ~ ", paste(input$indep_cox, collapse = "+"), sep = "")))
} else {
return(as.formula(paste("survival::Surv(", input$time_cox, ",", input$event_cox, ") ~ ", paste(input$indep_cox, collapse = "+"), " + cluster(", id.cluster(), ")", sep = "")))
}
})
out <- reactive({
req(!is.null(input$event_cox))
req(!is.null(input$time_cox))
data.cox <- data()
if (input$check_rangetime == T) {
req(input$time_cox)
data.cox <- data.cox[!(get(input$time_cox) < input$range_time[1])]
data.cox[[input$event_cox]] <- ifelse(data.cox[[input$time_cox]] >= input$range_time[2] & data.cox[[input$event_cox]] == "1", 0, as.numeric(as.vector(data.cox[[input$event_cox]])))
data.cox[[input$time_cox]] <- ifelse(data.cox[[input$time_cox]] >= input$range_time[2], input$range_time[2], data.cox[[input$time_cox]])
}
data.cox[[input$event_cox]] <- as.numeric(as.vector(data.cox[[input$event_cox]]))
label.regress <- data_label()
if (input$subcheck == T) {
validate(
need(length(input$subvar_cox) > 0, "No variables for subsetting"),
need(all(sapply(1:length(input$subvar_cox), function(x) {
length(input[[paste0("subval_cox", x)]])
})), "No value for subsetting")
)
for (v in seq_along(input$subvar_cox)) {
if (input$subvar_cox[[v]] %in% vlist()$factor_vars) {
data.cox <- data.cox[get(input$subvar_cox[[v]]) %in% input[[paste0("subval_cox", v)]]]
} else {
data.cox <- data.cox[get(input$subvar_cox[[v]]) >= input[[paste0("subval_cox", v)]][1] & get(input$subvar_cox[[v]]) <= input[[paste0("subval_cox", v)]][2]]
}
}
data.cox[, (vlist()$factor_vars) := lapply(.SD, factor), .SDcols = vlist()$factor_vars]
label.regress2 <- mk.lev(data.cox)[, c("variable", "level")]
data.table::setkey(data_label(), "variable", "level")
data.table::setkey(label.regress2, "variable", "level")
label.regress <- data_label()[label.regress2]
data.cox[[input$event_cox]] <- as.numeric(as.vector(data.cox[[input$event_cox]]))
}
mf <- model.frame(form.cox(), data.cox)
validate(
need(nrow(mf) > 0, paste("No complete data due to missingness. Please remove some variables from independent variables"))
)
lgl.1level <- purrr::map_lgl(mf, ~ length(unique(.x)) == 1)
validate(
need(sum(lgl.1level) == 0, paste(paste(names(lgl.1level)[lgl.1level], collapse = " ,"), "has(have) a unique value. Please remove that from independent variables"))
)
if (is.null(design.survey)) {
if (is.null(id.cluster)) {
cc <- substitute(survival::coxph(.form, data = data.cox, model = T, ties = .ties), list(.form = form.cox(), .ties = ties.coxph))
} else {
cc <- substitute(survival::coxph(.form, data = data.cox, model = T, robust = T, ties = .ties), list(.form = form.cox(), .ties = ties.coxph))
}
res.cox <- eval(cc)
if (input$step_check == T) {
validate(
need(!is.null(input$step_upper), "Upper limits can't be NULL, please select at least 1 variable."),
need(length((setdiff(input$step_lower, input$step_upper))) == 0, "Upper limits must include lower limits. Please add the variables to upper limits")
)
scope <- lapply(list(input$step_upper, input$step_lower), function(x) {
as.formula(ifelse(is.null(x), "~1", paste0("~", paste(x, collapse = "+"))))
})
data.cox.step <<- data.cox[complete.cases(data.cox[, .SD, .SDcols = c(input$time_cox, input$event_cox, input$indep_cox)])]
if (is.null(id.cluster)) {
cc.step <- substitute(survival::coxph(.form, data = data.cox.step, model = T, ties = .ties), list(.form = form.cox(), .ties = ties.coxph))
} else {
cc.step <- substitute(survival::coxph(.form, data = data.cox.step, model = T, robust = T, ties = .ties), list(.form = form.cox(), .ties = ties.coxph))
}
res.cox <- stats::step(eval(cc.step), direction = input$step_direction, scope = list(upper = scope[[1]], lower = scope[[2]]))
}
tb.cox <- jstable::cox2.display(res.cox, dec = input$decimal)
tb.cox <- jstable::LabeljsCox(tb.cox, ref = label.regress)
out.cox <- rbind(tb.cox$table, tb.cox$metric)
sig <- out.cox[, ncol(out.cox)]
sig <- gsub("< ", "", sig)
sig <- ifelse(as.numeric(as.vector(sig)) <= 0.05, "**", NA)
out.cox <- cbind(out.cox, sig)
if (is.null(id.cluster)) {
cap.cox <- paste("Cox's proportional hazard model on time ('", label.regress[variable == input$time_cox, var_label][1], "') to event ('", label.regress[variable == input$event_cox, var_label][1], "')", sep = "")
} else {
cap.cox <- paste("Marginal cox model on time ('", label.regress[variable == input$time_cox, var_label][1], "') to event ('", label.regress[variable == input$event_cox, var_label][1], "')", sep = "")
}
if (input$subcheck == T) {
for (v in seq_along(input$subvar_cox)) {
if (input$subvar_cox[[v]] %in% vlist()$factor_vars) {
cap.cox <- paste(cap.cox, ", ", label.regress[variable == input$subvar_cox[[v]], var_label][1], ": ", paste(label.regress[variable == input$subvar_cox[[v]] & level %in% input[[paste0("subval_cox", v)]], val_label], collapse = ", "), sep = "")
} else {
cap.cox <- paste(cap.cox, ", ", label.regress[variable == input$subvar_cox[[v]], var_label][1], ": ", paste(input[[paste0("subval_cox", v)]], collapse = "~"), sep = "")
}
}
}
if (input$step_check == T) {
cap.cox <- paste0(cap.cox, "- stepwise selection")
}
} else {
data.design <- design.survey()
if (input$check_rangetime == T) {
data.design <- subset(data.design, !(get(input$time_cox) < input$range_time[1]))
data.design$variables[[input$event_cox]] <- ifelse(data.design$variables[[input$time_cox]] >= input$range_time[2] & data.design$variables[[input$event_cox]] == "1", 0, as.numeric(as.vector(data.design$variables[[input$event_cox]])))
data.design$variables[[input$time_cox]] <- ifelse(data.design$variables[[input$time_cox]] >= input$range_time[2], input$range_time[2], data.design$variables[[input$time_cox]])
}
data.design$variables[[input$event_cox]] <- as.numeric(as.vector(data.design$variables[[input$event_cox]]))
if (input$subcheck == T) {
validate(
need(length(input$subvar_cox) > 0, "No variables for subsetting"),
need(all(sapply(1:length(input$subvar_cox), function(x) {
length(input[[paste0("subval_cox", x)]])
})), "No value for subsetting")
)
for (v in seq_along(input$subvar_cox)) {
if (input$subvar_cox[[v]] %in% vlist()$factor_vars) {
data.design <- subset(data.design, get(input$subvar_cox[[v]]) %in% input[[paste0("subval_cox", v)]])
} else {
data.design <- subset(data.design, get(input$subvar_cox[[v]]) >= input[[paste0("subval_cox", v)]][1] & get(input$subvar_cox[[v]]) <= input[[paste0("subval_cox", v)]][2])
}
}
data.design$variables[, (vlist()$factor_vars) := lapply(.SD, factor), .SDcols = vlist()$factor_vars]
label.regress2 <- mk.lev(data.design$variables)[, c("variable", "class", "level")]
data.table::setkey(data_label(), "variable", "class", "level")
data.table::setkey(label.regress2, "variable", "class", "level")
label.regress <- data_label()[label.regress2]
data.design$variables[[input$event_cox]] <- as.numeric(as.vector(data.design$variables[[input$event_cox]]))
}
cc <- substitute(survey::svycoxph(.form, design = data.design), list(.form = form.cox()))
res.cox <- eval(cc)
if (input$step_check == T) {
validate(
need(is.null(design.survey), "Survey cox model can't support stepwise selection")
)
}
tb.cox <- jstable::svycox.display(res.cox, decimal = input$decimal)
tb.cox <- jstable::LabeljsCox(tb.cox, label.regress)
out.cox <- rbind(tb.cox$table, tb.cox$metric)
sig <- out.cox[, ncol(out.cox)]
sig <- gsub("< ", "", sig)
sig <- ifelse(as.numeric(as.vector(sig)) <= 0.05, "**", NA)
out.cox <- cbind(out.cox, sig)
cap.cox <- paste("Weighted cox's proportional hazard model on time ('", label.regress[variable == input$time_cox, var_label][1], "') to event ('", label.regress[variable == input$event_cox, var_label][1], "') ", sep = "")
if (input$subcheck == T) {
for (v in seq_along(input$subvar_cox)) {
if (input$subvar_cox[[v]] %in% vlist()$factor_vars) {
cap.cox <- paste(cap.cox, ", ", label.regress[variable == input$subvar_cox[[v]], var_label][1], ": ", paste(label.regress[variable == input$subvar_cox[[v]] & level %in% input[[paste0("subval_cox", v)]], val_label], collapse = ", "), sep = "")
} else {
cap.cox <- paste(cap.cox, ", ", label.regress[variable == input$subvar_cox[[v]], var_label][1], ": ", paste(input[[paste0("subval_cox", v)]], collapse = "~"), sep = "")
}
}
}
}
return(list(table = out.cox, caption = cap.cox))
})
return(out)
}
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