addCov.Lexis | R Documentation |
When follow-up in a multistate model is represented in a
Lexis
object we may want to add information on
covariates, for example clinical measurements, obtained at different
times. This function cuts the follow-up time (see
cutLexis
) at the times of measurement and carries the
measurements forward in time to the next measurement occasion.
## S3 method for class 'Lexis'
addCov(Lx,
clin,
timescale = 1,
exnam,
tfc = "tfc", ...)
Lx |
A Lexis object with follow-up of a cohort. |
clin |
A data frame with covariates to add (typically clinical
measurements). Must contain a variable The times must be unique within each person; if not records with
duplicate times are discarded, and a warning issued. This is done
using |
timescale |
Numerical or character. Number or name of a timescale in
|
exnam |
Character. Name of the variable in |
tfc |
Character ( If the argument is omitted a variable called |
... |
Arguments passed on. Ignored |
A Lexis
object representing the same follow-up as Lx
,
with cuts added at the times of examination, and covariate
measurements added for all records representing follow-up after the
most recent time of measurement.
Also tfc
is added as a time scale, it is however not a proper
timescale since it is reset at every clinical examination. Therefor
the value of the timeSince
attribute is set to "X" in order
to distinguish it from other proper time scales that either have an
empty string or the name of a state.
Bendix Carstensen, b@bxc.dk, http://bendixcarstensen.com
cutLexis
,
mcutLexis
,
splitLexis
,
Lexis
# A small bogus cohort
xcoh <- structure( list( id = c("A", "B", "C"),
birth = c("1952-07-14", "1954-04-01", "1987-06-10"),
entry = c("1965-08-04", "1972-09-08", "1991-12-23"),
exit = c("1997-06-27", "1995-05-23", "1998-07-24"),
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 )
xcoh$en <- cal.yr( xcoh$entry )
xcoh$ex <- cal.yr( xcoh$exit )
# 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 = factor( fail, 0:1, c("Alive","Dead") ),
data = xcoh )
str( Lcoh )
Lx <- Lcoh[,1:7]
# Data frame with clinical examination data, date of examination in per
clin <- data.frame(lex.id = c(1,1,3,2),
per = cal.yr(c("1977-4-7",
"1971-7-1",
"1996-2-15",
"1990-7-3")),
bp = c(120,140,160,157),
chol = c(5,7,8,9),
xnam = c("X2","X1","X1","X2") )
Lx
clin
str(Lx)
str(clin)
# Different behavours when using exnam explicitly
addCov.Lexis( Lx, clin[,-5] )
addCov.Lexis( Lx, clin, exnam="xnam" )
# Works with time split BEFORE
Lb <- addCov.Lexis(splitLexis(Lx,
time.scale="age",
breaks=seq(0,80,5) ),
clin,
exnam="clX" )
Lb
# and also AFTER
La <- splitLexis(addCov.Lexis( Lx,
clin,
exnam = "xnam" ),
breaks=seq(0,80,5),
time.scale="age" )
La
La$tfc == Lb$tfc
La$age == Lb$age
str(La)
str(Lb)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.