

rmna(rmutil)                                 R Documentation

_C_r_e_a_t_e _a _r_e_p_e_a_t_e_d _o_b_j_e_c_t_, _r_e_m_o_v_i_n_g _N_A_s

_D_e_s_c_r_i_p_t_i_o_n_:

     `rmna' forms an object of class, repeated, from a
     response object and possibly time-varying covariate
     (tvcov), and time-constant covariate (tccov) objects,
     removing any response and covariate values that have
     NAs.

     Such objects can be printed and plotted.

_U_s_a_g_e_:

     rmna(response, tvcov=NULL, ccov=NULL)

_A_r_g_u_m_e_n_t_s_:

response: An object of class, response (created by
          `restovec'), containing the response variable
          information.

   tvcov: An object of class, tvcov (created by `tvctomat'),
          containing the time-varying covariate information.

   tccov: An object of class, tccov (created by `tcctomat'),
          containing the time-constant covariate informa-
          tion.

_V_a_l_u_e_:

     Returns an object of class, repeated, containing a list
     of the response object (z$response, so that, for exam-
     ple, the response vector is z$response$y; see
     `restovec'), and possibly the two classes of covariate
     objects (z$ccov and z$tvcov).

     Methods are available for extracting the response, the
     numbers of observations per individual, the times, the
     weights, the nesting variable, and the covariates or
     their names: `response', `nobs', `times', `weights',
     `nesting', `covariates', and `names'.

_A_u_t_h_o_r_(_s_)_:

     J.K. Lindsey

_S_e_e _A_l_s_o_:

     `carma', `elliptic', `gettvc', `kalcount', `kalseries',
     `nbkal', `read.list', `restovec', `tcctomat', `tvc-
     tomat'.

_E_x_a_m_p_l_e_s_:

     y <- matrix(rnorm(20),ncol=5)
     tt <- c(1,3,6,10,15)
     print(resp <- restovec(y,times=tt))
     x <- c(0,0,1,1)
     tcc <- tcctomat(x)
     z <- matrix(rpois(20,5),ncol=5)
     tvc <- tvctomat(z)
     print(reps <- rmna(resp, tvcov=tvc, ccov=tcc))
     response(reps)
     response(reps, nind=2:3)
     times(reps)
     nobs(reps)
     weights(reps)
     covariates(reps)
     covariates(reps,names="x")
     covariates(reps,names="z")
     names(reps)
     nesting(reps)
     # because individuals are the only nesting, this is the same as
     covind(reps)
     # binomial
     y <- matrix(rpois(20,5),ncol=5)
     print(respb <- restovec(y,totals=y+matrix(rpois(20,5),ncol=5),times=tt))
     print(repsb <- rmna(respb, tvcov=tvc, ccov=tcc))
     response(repsb)
     # censored data
     y <- matrix(rweibull(20,2,5),ncol=5)
     print(respc <- restovec(y,censor=matrix(rbinom(20,1,0.9),ncol=5),times=tt))
     print(repsc <- rmna(respc, tvcov=tvc, ccov=tcc))
     # if there is no censoring, censor indicator is not printed
     response(repsc)
     # nesting clustered within individuals
     nest <- c(1,1,2,2,2)
     print(respn <- restovec(y,censor=matrix(rbinom(20,1,0.9),ncol=5),
             times=tt,nest=nest))
     print(repsn <- rmna(respn, tvcov=tvc, ccov=tcc))
     response(respn)
     times(respn)
     nesting(respn)

