respdis               package:geepack               R Documentation

_C_l_u_s_t_e_r_e_d _O_r_d_i_n_a_l _R_e_s_p_i_r_a_t_o_r_y _D_i_s_o_r_d_e_r

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

     The 'respdis' data frame has 111 rows and 3 columns. The study
     described in Miller et. al. (1993) is a randomized clinical trial
     of a new treatment of respiratory disorder. The study was
     conducted in 111 patients who were randomly assigned to one of two
     treatments (active, placebo). At each of four visits during the
     follow-up period, the response status of each patients was
     classified on an ordinal scale.

_U_s_a_g_e:

     data(respdis)

_F_o_r_m_a_t:

     This data frame contains the following columns:

     _y_1, _y_2, _y_3, _y_4 ordered factor measured at 4 visits for the
          response with levels, '1' < '2' < '3', 1 = poor, 2 = good,
          and 3 = excellent

     _t_r_t a factor for treatment with levels, 1 = active, 0 = placebo.

_R_e_f_e_r_e_n_c_e_s:

     Miller, M.E., David, C.S., and Landis, R.J. (1993) The analysis of
     longitudinal polytomous data: Generalized estimating equation and
     connections with weighted least squares, _Biometrics_ *49*:
     1033-1048.

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

     data(respdis)
     resp.l <- reshape(respdis, varying = list(c("y1", "y2", "y3", "y4")),
                       v.names = "resp", direction = "long")
     resp.l <- resp.l[order(resp.l$id, resp.l$time),]
     fit <- ordgee(ordered(resp) ~ trt, id = id, data = resp.l, int.const = FALSE)
     summary(fit)

     z <- model.matrix( ~ trt - 1, data = respdis)
     ind <- rep(1:111, 4*3/2 * 2^2)
     zmat <- z[ind,,drop=FALSE]
     fit <- ordgee(ordered(resp) ~ trt, id = id, data = resp.l, int.const = FALSE,
                   z = zmat, corstr = "exchangeable")
     summary(fit)

