expand.covs.msdata  R Documentation 
Given a multistate dataset in long format, and one or more covariates, this function adds transitionspecific covariates, expanding the original covariate(s), to the dataset. The original dataset with the transitionspecific covariates appended is returned.
## S3 method for class 'msdata'
expand.covs(data, covs, append = TRUE, longnames = TRUE, ...)
data 
An object of class 
covs 
A character vector containing the names of the covariates in

append 
Logical value indicating whether or not the design matrix for
the expanded covariates should be appended to the data (default= 
longnames 
Logical value indicating whether or not the labels are to
be used for the names of the expanded covariates that are categorical
(default= 
... 
Further arguments to be passed to or from other methods. They are ignored in this function. 
For a given basic covariate Z
, the transitionspecific covariate for
transition s
is called Z.s
. The concept of transitionspecific
covariates in the context of multistate models was introduced by Andersen,
Hansen & Keiding (1991), see also Putter, Fiocco & Geskus (2007). It is only
unambiguously defined for numeric covariates or for explicit codings. Then
it will take the value 0 for all rows in the long format dataframe for which
trans
does not equal s
. For the rows for which trans
equals s
, the original value of Z
is copied. In
expand.covs
, when a given covariate is a factor, it will be expanded
on the design matrix given by
model.matrix
. Missing values in the basic
covariates are allowed and result in missing values in the expanded
covariates.
An object of class 'msdata', containing the design matrix for the
transition specific covariates, either on its own
(append
=FALSE
) or appended to the data
(append
=TRUE
).
Hein Putter H.Putter@lumc.nl
Andersen PK, Hansen LS, Keiding N (1991). Non and semiparametric estimation of transition probabilities from censored observation of a nonhomogeneous Markov process. Scandinavian Journal of Statistics 18, 153–167.
Putter H, Fiocco M, Geskus RB (2007). Tutorial in biostatistics: Competing risks and multistate models. Statistics in Medicine 26, 2389–2430.
# transition matrix for illnessdeath model
tmat < trans.illdeath()
# small data set in wide format
tg < data.frame(illt=c(1,1,6,6,8,9),ills=c(1,0,1,1,0,1),
dt=c(5,1,9,7,8,12),ds=c(1,1,1,1,1,1),
x1=c(1,1,1,2,2,2),x2=c(6:1))
tg$x1 < factor(tg$x1,labels=c("male","female"))
# data in long format using msprep
tglong < msprep(time=c(NA,"illt","dt"),
status=c(NA,"ills","ds"),data=tg,
keep=c("x1","x2"),trans=tmat)
# expanded covariates
expand.covs(tglong,c("x1","x2"),append=FALSE)
expand.covs(tglong,"x1")
expand.covs(tglong,"x1",longnames=FALSE)
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