

potthoff(growth)                             R Documentation

_P_o_t_t_h_o_f_f _a_n_d _R_o_y _g_r_o_w_t_h _c_u_r_v_e _m_o_d_e_l

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

     `potthoff' fits the Potthoff and Roy repeated measure-
     ments growth curve model with unstructured covariance
     matrix to completely balanced data.

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

     potthoff(response, x, ccov=NULL, times=NULL, torder=0, orthogonal=T)

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

response: A matrix or dataframe of response values.

       x: A matrix defining the complete intersubject dif-
          ferences.

    ccov: A matrix of columns of the baseline covariates to
          be actually fitted, with one row per individual.

   times: A vector of unequally spaced times when they are
          the same for all individuals. Not necessary if
          equally spaced.

  torder: Order of the polynomial in time to be fitted. If
          non-numeric, the full model in time is fitted.

orthogonal: If TRUE, uses orthogonal polynomials for time,
          otherwise only centres times at their mean.

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

     A list of class potthoff is returned.

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

     J.K. Lindsey

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

     `carma', `elliptic', `lm'.

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

     y <- matrix(rnorm(40),ncol=5)
     x <- gl(2,4)
     # full model with treatment effect
     potthoff(y, ~x, torder="f", ccov=~x)
     # no time trend with treatment effect
     potthoff(y, ~x, torder=0, ccov=~x)
     # quadratic time with treatment effect
     potthoff(y, ~x, torder=2, ccov=~x)
     # full model without treatment effect
     potthoff(y, ~x, torder="f")
     # linear time without treatment effect
     potthoff(y, ~x, torder=1)

