tvctomat {rmutil} | R Documentation |
tvctovmat
creates an object of class, tvcov, from a list of
matrices with time-varying covariates for each individual or one
matrix or dataframe of such covariate values or combines two such
objects. It can also add interactions among covariates.
Such objects can be printed. Methods are available for extracting the
covariates and their names: covariates
and names
. The
method, link{transform}
, can transform variables in place or by
adding new variables to the object.
tvctomat(tvcov, names=NULL, interaction=NULL, ccov=NULL, oldtvcov=NULL, dataframe=TRUE)
tvcov |
A list of matrices with time-varying covariate values for each individual (one column per variable), one matrix or dataframe of such covariate values (when there is only one such covariate), or an object of class, tvcov. In the first two cases, the variables may be factors. |
names |
The names of the time-varying covariates in tvcov (if the matrices do not have column names) or the names of the time-constant covariates for interactions. |
interaction |
A pair of index numbers or names of variables in tvcov,
with that class, for which an interaction is to be added or, if
ccov is provided, a set of such names of time-varying
covariates for creating interactions with the time-constant covariates. |
ccov |
Time-constant covariates for which an interaction is to be introduced with time-varying covariates in tvcov. |
oldtvcov |
An object of class, tvcov, to which tvcov is to be added. |
dataframe |
If TRUE and factor variables are present, the covariates are stored as a dataframe; if FALSE, they are expanded to indicator variables. If no factor variables are present, covariates are always stored as a matrix. |
Returns an object of class, tvcov, containing a matrix for the covariates (z$tvcov) with one row per response per individual and a vector giving the number of observations per individual (z$nobs).
J.K. Lindsey
gettvc
, read.list
, restovec
,
rmna
, tcctomat
, transform
.
z <- matrix(rpois(20,5),ncol=5) print(tvc <- tvctomat(z)) covariates(tvc) names(tvc) v <- data.frame(matrix(rep(c("a","b","c","d","e"),4),ncol=5)) print(tvc2 <- tvctomat(v, oldtvc=tvc)) covariates(tvc2) print(tvc3 <- tvctomat(v, oldtvc=tvc, dataframe=T)) covariates(tvc3) print(tvc4 <- tvctomat(tvc3, interaction=c("z","v"))) covariates(tvc4) x1 <- 1:4 x2 <- gl(4,1) xx <- tcctomat(data.frame(x1,x2)) tvctomat(tvc3, interaction="z", ccov=xx) tvctomat(tvc3, interaction="z", ccov=xx, names="x1") tvctomat(tvc3, interaction="z", ccov=xx, names=c("x22","x23","x24")) xx <- tcctomat(data.frame(x1,x2), dataframe=T) tvctomat(tvc3, interaction="z", ccov=xx) tvctomat(tvc3, interaction="z", ccov=xx, names="x1") tvctomat(tvc3, interaction="z", ccov=xx, names="x2")