potthoff               package: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 measurements 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=TRUE)

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

response: A matrix or dataframe of response values.

       x: A matrix defining the complete intersubject differences or a
          Wilkinson and Rogers formula that will create one.

    ccov: A matrix of columns of the baseline covariates to be actually
          fitted, with one row per individual or a W&R formula that
          will create one.

   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)

