corCompSymm               package:nlme               R Documentation

_C_o_m_p_o_u_n_d _S_y_m_m_e_t_r_y _C_o_r_r_e_l_a_t_i_o_n _S_t_r_u_c_t_u_r_e

_D_e_s_c_r_i_p_t_i_o_n:

     This function is a constructor for the 'corCompSymm' class,
     representing a compound symmetry structure corresponding to
     uniform correlation. Objects created using this constructor must
     later be initialized using the appropriate 'Initialize' method.

_U_s_a_g_e:

     corCompSymm(value, form, fixed)

_A_r_g_u_m_e_n_t_s:

   value: the correlation between any two correlated observations.
          Defaults to 0.

    form: a one sided formula of the form '~ t', or '~ t | g',
          specifying a time covariate 't' and,  optionally, a grouping
          factor 'g'. When a grouping factor is present in 'form', the
          correlation structure is assumed to apply only to
          observations within the same grouping level; observations
          with different grouping levels are assumed to be
          uncorrelated. Defaults to '~ 1', which corresponds to using
          the order of the observations in the data as a covariate, and
          no groups.

   fixed: an optional logical value indicating whether the coefficients
          should be allowed to vary in the optimization, or kept fixed
          at their initial value. Defaults to 'FALSE', in which case
          the coefficients are allowed to vary.

_V_a_l_u_e:

     an object of class 'corCompSymm', representing a compound symmetry
     correlation structure.

_A_u_t_h_o_r(_s):

     Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates
     bates@stat.wisc.edu

_R_e_f_e_r_e_n_c_e_s:

     Milliken, G. A. and Johnson, D. E. (1992) "Analysis of Messy Data,
     Volume I: Designed Experiments", Van Nostrand Reinhold.

     Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models in S
     and S-PLUS", Springer, esp. pp. 233-234.

_S_e_e _A_l_s_o:

     'corClasses',  'Initialize.corStruct', 'summary.corStruct'

_E_x_a_m_p_l_e_s:

     ## covariate is observation order and grouping factor is Subject
     cs1 <- corCompSymm(0.5, form = ~ 1 | Subject)

     # Pinheiro and Bates, pp. 222-225 
     fm1BW.lme <- lme(weight ~ Time * Diet, BodyWeight,
                        random = ~ Time)
     # p. 223
     fm2BW.lme <- update(fm1BW.lme, weights = varPower())
     # p. 225
     cs1CompSymm <- corCompSymm(value = 0.3, form = ~ 1 | Subject)
     cs2CompSymm <- corCompSymm(value = 0.3, form = ~ age | Subject)
     cs1CompSymm <- Initialize(cs1CompSymm, data = Orthodont)
     corMatrix(cs1CompSymm)

