R: Visualise multiple probtrans objects

vis.multiple.pt {mstate} | R Documentation

## Visualise multiple probtrans objects

### Description

Helper function allow to visualise state probabilities for different reference patients/covariates. Multiple `"probtrans"` objects are thus needed.

### Usage

    vis.multiple.pt(
      x,
      from = 1,
      to,
      xlab = "Time",
      ylab,
      xlim = NULL,
      ylim = NULL,
      cols,
      lwd,
      labels,
      conf.int = 0.95,
      conf.type = c("log", "plain", "none"),
      legend.title
    )

### Arguments

`x` | A list of `"probtrans"` objects
`from` | The starting state from which the probabilities are used to plot Numeric, as in `plot.probtrans`
`to` | (Numeric) destination state
`xlab` | A title for the x-axis; default is `"Time"`
`ylab` | A title for the y-axis; default is `"Probability"`
`xlim` | The x limits of the plot(s), default is range of time
`ylim` | The y limits of the plot(s); if ylim is specified for type="separate", then all plots use the same ylim for y limits
`cols` | A vector specifying colors for the different transitions; default is a palette from green to red, when type=`"filled"` (reordered according to `ord`, and 1 (black), otherwise
`lwd` | The line width, see `par`; default is 1
`labels` | Character vector labelling each element of x (e.g. label for a reference patient) - so labels = c("Patient 1", "Patient 2")
`conf.int` | Confidence level (%) from 0-1 for probabilities, default is 0.95 (95% CI). Setting to 0 removes the CIs.
`conf.type` | Type of confidence interval - either "log" or "plain" . See function details for details.
`legend.title` | Character - title of legend

### Value

A ggplot object.

### Author(s)

Edouard F. Bonneville e.f.bonneville@lumc.nl

### Examples

    library(ggplot2)

    data("aidssi")
    head(aidssi)
    si <- aidssi

    # Prepare transition matrix
    tmat <- trans.comprisk(2, names = c("event-free", "AIDS", "SI"))

    # Run msprep
    si$stat1 <- as.numeric(si$status == 1)
    si$stat2 <- as.numeric(si$status == 2)

    silong <- msprep(
    time = c(NA, "time", "time"),
    status = c(NA, "stat1", "stat2"),
    data = si, keep = "ccr5", trans = tmat
    )

    # Run cox model
    silong <- expand.covs(silong, "ccr5")
    c1 <- coxph(Surv(time, status) ~ ccr5WM.1 + ccr5WM.2 + strata(trans),
                data = silong)

    # 1. Prepare patient data - both CCR5 genotypes
    WW <- data.frame(
    ccr5WM.1 = c(0, 0),
    ccr5WM.2 = c(0, 0),
    trans = c(1, 2),
    strata = c(1, 2)
    )

    WM <- data.frame(
    ccr5WM.1 = c(1, 0),
    ccr5WM.2 = c(0, 1),
    trans = c(1, 2),
    strata = c(1, 2)
    )

    # 2. Make msfit objects
    msf.WW <- msfit(c1, WW, trans = tmat)
    msf.WM <- msfit(c1, WM, trans = tmat)

    # 3. Make probtrans objects
    pt.WW <- probtrans(msf.WW, predt = 0)
    pt.WM <- probtrans(msf.WM, predt = 0)

    # Plot - see vignette for more details
    vis.multiple.pt(
    x = list(pt.WW, pt.WM),
    from = 1,
    to = 2,
    conf.type = "log",
    cols = c(1, 2),
    labels = c("Pat WW", "Pat WM"),
    legend.title = "Ref patients"
    )

[Package mstate version 0.3.1 Index]