hchart.survfit {psichomics} | R Documentation

## Plot survival curves

### Description

Plot survival curves

### Usage

    ## S3 method for class 'survfit'
    hchart(
      object,
      ...,
      fun = NULL,
      markTimes = TRUE,
      symbol = "plus",
      markerColor = "black",
      ranges = FALSE,
      rangesOpacity = 0.3
    )

### Arguments

`object` | `survfit` object as returned from `survfit.survTerms()` function
`...` | Arguments passed on to `highcharter::hc_add_series`
`fun` | Name of function or function used to transform the survival curve: `log` will put y axis on log scale, `event` plots cumulative events (f(y) = 1-y), `cumhaz` plots the cumulative hazard function (f(y) = -log(y)), and `cloglog` creates a complimentary log-log survival plot (f(y) = log(-log(y)) along with log scale for the x-axis.
`markTimes` | Label curves marked at each censoring time?
`symbol` | Symbol to use as marker
`markerColor` | Colour of the marker; if `NULL`, the respective colour of each series are used
`ranges` | Plot interval ranges?
`rangesOpacity` | Opacity of the interval ranges

### Value

`highchart` object to plot survival curves

### Examples

    # Plot Kaplan-Meier curves
    require("survival")
    require("highcharter")
    leukemia.surv <- survfit(Surv(time, status) ~ x, data = aml)
    hchart(leukemia.surv)

    # Plot the cumulative hazard function
    lsurv2 <- survfit(Surv(time, status) ~ x, aml, type='fleming')
    hchart(lsurv2, fun="cumhaz")

    # Plot the fit of a Cox proportional hazards regression model
    fit <- coxph(Surv(futime, fustat) ~ age, data = ovarian)
    ovarian.surv <- survfit(fit, newdata=data.frame(age=60))
    hchart(ovarian.surv, ranges = TRUE)

[Package psichomics version 1.20.2 Index]