Shiny module server for kaplan-meier plot.
Usage
kaplanModule(
input,
output,
session,
data,
data_label,
data_varStruct = NULL,
nfactor.limit = 10,
design.survey = NULL,
id.cluster = NULL,
timeby = NULL,
range.x = NULL,
range.y = NULL,
vec.event = NULL,
vec.time = NULL
)
Arguments
- input
input
- output
output
- session
session
- data
Reactive data
- data_label
Reactive data label
- data_varStruct
Reactive List of variable structure, Default: NULL
- nfactor.limit
nlevels limit in factor variable, Default: 10
- design.survey
Reactive survey data. default: NULL
- id.cluster
Reactive cluster variable if marginal model, Default: NULL
- timeby
timeby, Default: NULL
- range.x
range of x axis, Default: NULL
- range.y
range of y axis, Default: NULL
- vec.event
event variables as vector for survival analysis, Default: NULL
- vec.time
time variables as vector for survival analysis, Default: NULL
Examples
library(shiny)
library(DT)
library(data.table)
library(jstable)
library(ggplot2)
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
kaplanUI("kaplan")
),
mainPanel(
plotOutput("kaplan_plot"),
ggplotdownUI("kaplan")
)
)
)
server <- function(input, output, session) {
data <- reactive(mtcars)
data.label <- reactive(jstable::mk.lev(mtcars))
out_kaplan <- callModule(kaplanModule, "kaplan",
data = data, data_label = data.label,
data_varStruct = NULL
)
output$kaplan_plot <- renderPlot({
print(out_kaplan())
})
}