R: Mirror plot comparing two probtrans objects

vis.mirror.pt {mstate} | R Documentation

## Mirror plot comparing two probtrans objects

### Description

A mirror plot for comparing two different `"probtrans"` objects. Useful for comparing predicted probabilities for different levels of a covariate, or for different subgroups.

### Usage

    vis.mirror.pt(
      x,
      titles,
      size_titles = 5,
      horizon = NULL,
      breaks_x_left,
      breaks_x_right,
      from = 1,
      cols,
      ord,
      xlab = "Time",
      ylab = "Probability",
      legend.pos = "right"
    )

### Arguments

`x` | A list of two `"probtrans"` objects. The first element will be on the left of the mirror plot, and the second on the right
`titles` | A character vector c("Title for left", "Title for right")
`size_titles` | Numeric, size of the title text
`horizon` | Numeric, position denoting (in time) where to symmetrically mirror the plots. Default is maximum follow-up of from both plots.
`breaks_x_left` | Numeric vector specifying axis breaks on the left plot
`breaks_x_right` | Numeric vector specifying axis breaks on the right plot
`from` | The starting state from which the probabilities are used to plot
`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
`ord` | A vector of length equal to the number of states, specifying the order of plotting in case type=`"stacked"` or `"filled"`
`xlab` | A title for the x-axis, default is "Time"
`ylab` | A title for the y-axis, default is "Probability"
`legend.pos` | Position of the legend, default is "right"

### Value

A ggplot2 object.

### Author(s)

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

### See Also

`plot.probtrans`

### 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 reference 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)

    # Mirror plot split at 10 years - see vignette for more details
    vis.mirror.pt(
    x = list(pt.WW, pt.WM),
    titles = c("WW", "WM"),
    horizon = 10
    )

[Package mstate version 0.3.1 Index]