plot.mvna {mvna} | R Documentation |
Plot method for an object of class mvna
. This function plots
estimates of the cumulative transition hazards in one panel.
## S3 method for class 'mvna' plot(x, tr.choice, xlab = "Time", ylab = "Cumulative Hazard", col = 1, lty, xlim, ylim, conf.int = FALSE, level = 0.95, var.type = c("aalen", "greenwood"), ci.fun = c("log", "linear", "arcsin"), ci.col = col, ci.lty = 3, legend = TRUE, legend.pos, curvlab, legend.bty = "n", ...)
x |
An object of class |
tr.choice |
A character vector of the form |
xlab |
x-axis label. Default is "Time". |
ylab |
y-axis label. Default is "Cumulative Hazard". |
col |
Vector of colour. Default is black. |
lty |
Vector of line type. Default is 1:number of transitions |
xlim |
Limits of x-axis for the plot |
ylim |
Limits of y-axis for the plot |
conf.int |
Logical. Whether to display pointwise confidence intervals. Default is FALSE. |
level |
Level of the pointwise confidence intervals. Default is 0.95. |
var.type |
A character vector specifying the variance that should be used to compute the pointwise confidence intervals. Choices are "aalen" or "greenwood". Default is "aalen". |
ci.fun |
One of "log", "linear" or "arcsin". Indicates which transformation to apply to the confidence intervals. |
ci.col |
Colour for the confidence intervals. By default, the
colour specified by |
ci.lty |
Line type for the confidence intervals. Default is 3. |
legend |
A logical specifying if a legend should be added |
legend.pos |
A vector giving the legend's position. See
|
curvlab |
A character or expression vector to appear in the legend. Default is the name of the transitions. |
legend.bty |
Box type for the legend. |
... |
Further arguments for plot method. |
This plot method permits to draw several cumulative transition hazards on the same panel.
No value returned
Arthur Allignol arthur.allignol@gmail.com
data(sir.cont) # Modification for patients entering and leaving a state # at the same date sir.cont <- sir.cont[order(sir.cont$id, sir.cont$time), ] for (i in 2:nrow(sir.cont)) { if (sir.cont$id[i]==sir.cont$id[i-1]) { if (sir.cont$time[i]==sir.cont$time[i-1]) { sir.cont$time[i-1] <- sir.cont$time[i-1] - 0.5 } } } tra <- matrix(ncol=3,nrow=3,FALSE) tra[1, 2:3] <- TRUE tra[2, c(1, 3)] <- TRUE na.cont <- mvna(sir.cont,c("0","1","2"),tra,"cens") plot(na.cont, tr.choice=c("0 2", "1 2"))