

   CCrreeaattee oorr aadddd ttoo aa ttiimmee--ccoonnssttaanntt ccoovvaarriiaattee ((ttccccoovv)) oobbjjeecctt

        tcctomat(ccov, names=NULL, oldccov=NULL, dataframe=TRUE)

   AArrgguummeennttss::

       ccov: A vector or matrix containing time-constant base-
             line covariates with one row per individual, a
             model formula using vectors of the same size, or
             an object of class, tccov.

      names: The names of the covariates (if the matrix does
             not have column names).

    oldccov: An object of class, tccov, to which ccov 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.

   DDeessccrriippttiioonn::

        `tcctomat' creates an object of class, tccov, from a
        vector or matrix containing time-constant baseline
        covariates or a model formula, or combines two such
        objects.

        Such objects can be printed. Methods are available for
        extracting the covariates, their names, and the for-
        mula: `covariates', `names', and `formula'. The method,
        `link{transform}', can transform variables in place or
        by adding new variables to the object.

        To obtain the indexing to expand time-constant covari-
        ates to the size of a repeated measurements response,
        use `covind'.

   VVaalluuee::

        Returns an object of class, tccov, containing one
        matrix for the covariates (z$ccov) with one row per
        individual and possibly the model formula (z$linear).

   AAuutthhoorr((ss))::

        J.K. Lindsey

   SSeeee AAllssoo::

        `read.list', `restovec', `rmna', `transform', `tvc-
        tomat'.

   EExxaammpplleess::

        x1 <- gl(4,1)
        print(tcc1 <- tcctomat(~x1))
        covariates(tcc1)
        covariates(tcc1, name="x12")
        tcctomat(x1)
        tcctomat(x1, dataframe=T)
        x2 <- c(0,0,1,1)
        print(tcc2 <- tcctomat(~x2))
        covariates(tcc2)
        print(tcc3 <- tcctomat(~x1+x2))
        covariates(tcc3)
        covariates(tcc3, names=c("x12","x2"))
        formula(tcc3)
        names(tcc3)
        print(tcc4 <- tcctomat(data.frame(x1,x2)))
        covariates(tcc4)
        print(tcc5 <- tcctomat(data.frame(x1,x2), dataframe=T))
        covariates(tcc5)

