Lexis diagrams
The follow-up histories represented by a Lexis object can be plotted using one or two dimensions. The two dimensional plot is a Lexis diagram showing follow-up time simultaneously on two time scales.
## S3 method for class 'Lexis'
plot(x=Lexis( entry=list(Date=1900,Age=0), exit=list(Age=0) ),
time.scale = NULL, type="l", breaks="lightgray", ...)
## S3 method for class 'Lexis'
points(x, time.scale = options()[["Lexis.time.scale"]] , ...)
## S3 method for class 'Lexis'
lines(x, time.scale = options()[["Lexis.time.scale"]], ...)
## S3 method for class 'Lexis'
PY.ann(x, time.scale = options()[["Lexis.time.scale"]], digits=1, ...)x |
An object of class |
time.scale |
A vector of length 1 or 2 giving the time scales to be plotted either by name or numerical order |
type |
Character indication what to draw: "n" nothing (just set up the diagram), "l" - liefelines, "p" - endpoints of follow-up, "b" - both lifelines and endpoints. |
breaks |
a string giving the colour of grid lines to be drawn
when plotting a split Lexis object. Grid lines can be suppressed by
supplying the value |
digits |
Numerical. How many digits after the demimal points should be when plotting the person-years. |
... |
Further graphical parameters to be passed to the plotting methods. Grids can be drawn (behind the life lines) using the following
parameters in
|
The plot method for Lexis objects traces “life lines” from
the start to the end of follow-up. The points method plots
points at the end of the life lines.
If time.scale is of length 1, the life lines are drawn
horizontally, with the time scale on the X axis and the id value on the Y
axis. If time.scale is of length 2, a Lexis diagram is
produced, with diagonal life lines plotted against both time scales
simultaneously.
If lex has been split along one of the time axes by a call to
splitLexis, then vertical or horizontal grid lines are plotted
(on top of the life lines) at the break points.
PY.ann writes the length of each (segment of) life line at the middle
of the line. Not advisable to use with large cohorts. Another example is
in the example file for occup.
Martyn Plummer
# A small bogus cohort
xcoh <- structure( list( id = c("A", "B", "C"),
birth = c("14/07/1952", "01/04/1957", "10/06/1987"),
entry = c("04/08/1965", "08/09/1972", "23/12/1991"),
exit = c("27/06/1997", "23/05/1995", "24/07/1998"),
fail = c(1, 0, 1) ),
.Names = c("id", "birth", "entry", "exit", "fail"),
row.names = c("1", "2", "3"),
class = "data.frame" )
# Convert the character dates into numerical variables (fractional years)
xcoh$bt <- cal.yr( xcoh$birth, format="%d/%m/%Y" )
xcoh$en <- cal.yr( xcoh$entry, format="%d/%m/%Y" )
xcoh$ex <- cal.yr( xcoh$exit , format="%d/%m/%Y" )
# See how it looks
xcoh
# Define as Lexis object with timescales calendar time and age
Lcoh <- Lexis( entry = list( per=en ),
exit = list( per=ex, age=ex-bt ),
exit.status = fail,
data = xcoh )
# Default plot of follow-up
plot( Lcoh )
# Show follow-up time
PY.ann( Lcoh )
# Show exit status
plot( Lcoh, type="b" )
# Same but failures only
plot( Lcoh, type="b", pch=c(NA,16)[Lcoh$fail+1] )
# With a grid and deaths as endpoints
plot( Lcoh, grid=0:10*10, col="black" )
points( Lcoh, pch=c(NA,16)[Lcoh$lex.Xst+1] )
# With a lot of bells and whistles:
plot( Lcoh, grid=0:20*5, col="black", xaxs="i", yaxs="i",
xlim=c(1960,2010), ylim=c(0,50), lwd=3, las=1 )
points( Lcoh, pch=c(NA,16)[Lcoh$lex.Xst+1], col="red", cex=1.5 )Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.