plot.TPCmsm | R Documentation |
plot method for an object of class ‘TPCmsm’. It draws the estimated transition probabilities in a basic scatterplot.
## S3 method for class 'TPCmsm' plot(x, plot.type="t", tr.choice, xlab, ylab, col, lty, xlim, ylim, conf.int=FALSE, ci.col, ci.lty, legend=TRUE, legend.pos, curvlab, legend.bty="n", ...)
x |
An object of class ‘TPCmsm’. |
plot.type |
A character string specifying the type of plot. If “t” the scatterplot of transition probability versus time is plotted. If “c” the scatterplot of transition probability versus covariate is plotted. |
tr.choice |
Character vector of the form ‘c(“from to”, “from to”)’ specifying which transitions should be plotted. Default, all the transition probabilities are plotted. |
xlab |
x-axis label. |
ylab |
y-axis label. |
col |
Vector of colour. |
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 bands. Default is FALSE. |
ci.col |
Colour of the confidence bands. Default is |
ci.lty |
Line type of the confidence bands. 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. By default no box is drawn. |
... |
Further arguments for plot. |
No value is returned.
Artur Araújo, Javier Roca-Pardiñas and Luís Meira-Machado
Araújo A, Meira-Machado L, Roca-Pardiñas J (2014). TPmsm: Estimation of the Transition Probabilities in 3-State Models. Journal of Statistical Software, 62(4), 1-29. doi: 10.18637/jss.v062.i04
Meira-Machado L., de Uña-Álvarez J., Datta S. (2011). Conditional Transition Probabilities in a non-Markov Illness-death Model. Discussion Papers in Statistics and Operation Research n 11/03. Department of Statistics and Operations Research, University of Vigo (ISSN: 1888-5756, Deposito Legal VG 1402-2007). https://depc05.webs.uvigo.es/reports/12_05.pdf
legend
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plot.default
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# Set the number of threads nth <- setThreadsTP(2) # Create survTP object data(heartTP) heartTP_obj <- with( heartTP, survTP(time1, event1, Stime, event, age=age) ) # Compute IPCW conditional transition probabilities with confidence band TPCmsm_obj <- transIPCW(heartTP_obj, s=57, t=310, x=c(0, 15), conf=TRUE, n.boot=100, method.boot="percentile", method.est=2) # Build time plots tr.choice <- dimnames(TPCmsm_obj$est)[[3]] par.orig <- par( c("mfrow", "cex") ) par( mfrow=c(2,3) ) for ( i in seq_len( length(tr.choice) ) ) { plot(TPCmsm_obj, plot.type="t", tr.choice=tr.choice[i], conf.int=TRUE, legend=TRUE, main=tr.choice[i], col=seq_len( length(TPCmsm_obj$x) ), lty=1, xlab="", ylab="", curvlab=c("Age = 0", "Age = 15")) } par(mfrow=c(1, 1), cex=1.2) title(xlab="Time", ylab="Transition probability", line=3) par(par.orig) # Build covariate plots without colors and without confidence band plot(TPCmsm_obj, plot.type="c", xlab="Age") # Build covariate plots with colors and without confidence band plot(TPCmsm_obj, plot.type="c", col=seq_len(5), lty=1, xlab="Age") # Build covariate plots with confidence band tr.choice <- dimnames(TPCmsm_obj$est)[[3]] par.orig <- par( c("mfrow", "cex") ) par( mfrow=c(2,3) ) for ( i in seq_len( length(tr.choice) ) ) { plot(TPCmsm_obj, plot.type="c", tr.choice=tr.choice[i], conf.int=TRUE, legend=FALSE, main=tr.choice[i], xlab="", ylab="") } par(mfrow=c(1, 1), cex=1.2) title( xlab="Age", ylab=paste("P(", TPCmsm_obj$s, ", ", TPCmsm_obj$t, " | Age)", sep=""), line=3) par(par.orig) # Restore the number of threads setThreadsTP(nth)
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