Split follow-up time in a Lexis object
The splitLexis function divides each row of a Lexis
object into disjoint follow-up intervals according to the supplied
break points.
splitLexis(lex, breaks, time.scale, tol=.Machine$double.eps^0.5)
lex |
an object of class |
breaks |
a vector of break points |
time.scale |
the name or number of the time scale to be split |
tol |
numeric value >= 0. Intervals shorter than this value are dropped |
An object of class Lexis with multiple rows for each row of
the argument lex. Each row of the new Lexis object
contains the part of the follow-up interval that falls inside one of
the time bands defined by the break points.
The variables representing the various time scales, are appropriately
updated in the new Lexis object. The entry and exit status
variables are also updated according to the rule that the entry status
is retained until the end of follow-up. All other variables are
considered to represent variables that are constant in time, and so
are replicated across all rows having the same id value.
The splitLexis() function divides follow-up time into intervals
using breakpoints that are common to all rows of the Lexis object.
To split a Lexis object by break points that are unique to each
row, use the cut.Lexis function.
Martyn Plummer
# A small bogus cohort
xcoh <- structure( list( id = c("A", "B", "C"),
birth = c("14/07/1952", "01/04/1954", "10/06/1987"),
entry = c("04/08/1965", "08/09/1972", "23/12/1991"),
exit = c("27/06/1997", "23/05/1995", "24/07/1998"),
fail = c(1, 0, 1) ),
.Names = c("id", "birth", "entry", "exit", "fail"),
row.names = c("1", "2", "3"),
class = "data.frame" )
# Convert the character dates into numerical variables (fractional years)
xcoh$bt <- cal.yr( xcoh$birth, format="%d/%m/%Y" )
xcoh$en <- cal.yr( xcoh$entry, format="%d/%m/%Y" )
xcoh$ex <- cal.yr( xcoh$exit , format="%d/%m/%Y" )
# See how it looks
xcoh
# Define as Lexis object with timescales calendar time and age
Lcoh <- Lexis( entry = list( per=en ),
exit = list( per=ex, age=ex-bt ),
exit.status = fail,
data = xcoh )
# Default plot of follow-up
plot( Lcoh )
# With a grid and deaths as endpoints
plot( Lcoh, grid=0:10*10, col="black" )
points( Lcoh, pch=c(NA,16)[Lcoh$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 )
# Split time along two time-axes
( x2 <- splitLexis( Lcoh, breaks = seq(1900,2000,5), time.scale="per") )
( x2 <- splitLexis( x2, breaks = seq(0,80,5), time.scale="age" ) )
str( x2 )
# Tabulate the cases and the person-years
summary( x2 )
tapply( status(x2,"exit")==1, list( timeBand(x2,"age","left"),
timeBand(x2,"per","left") ), sum )
tapply( dur(x2), list( timeBand(x2,"age","left"),
timeBand(x2,"per","left") ), sum )Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.