comparePred               package:nlme               R Documentation

_C_o_m_p_a_r_e _P_r_e_d_i_c_t_i_o_n_s

_D_e_s_c_r_i_p_t_i_o_n:

     Predicted values are obtained at the specified values of 'primary'
     for each object. If either 'object1' or 'object2' have a grouping
     structure (i.e. 'getGroups(object)' is not 'NULL'), predicted
     values are obtained for each group. When both objects determine
     groups, the group levels must be the same. If other covariates
     besides 'primary' are used in the prediction model, their
     group-wise averages (numeric covariates) or most frequent values
     (categorical covariates) are used to obtain the predicted values.
     The original observations are also included in the returned
     object.

_U_s_a_g_e:

     comparePred(object1, object2, primary, minimum, maximum,
         length.out, level, ...)

_A_r_g_u_m_e_n_t_s:

object1,object2: fitted model objects, from which predictions can be
          extracted using the 'predict' method.

 primary: an optional one-sided formula specifying the primary
          covariate to be used to generate the augmented predictions.
          By default, if a  covariate can be extracted from the data
          used to generate the objects (using 'getCovariate'), it will
          be used as 'primary'.

 minimum: an optional lower limit for the primary covariate. Defaults
          to 'min(primary)', after 'primary' is  evaluated in the
          'data' used in fitting 'object1'.

 maximum: an optional upper limit for the primary covariate. Defaults
          to 'max(primary)', after 'primary' is evaluated in the 'data'
          used in fitting 'object1'.

length.out: an optional integer with the number of primary covariate
          values at which to evaluate the predictions. Defaults to 51.

   level: an optional integer specifying the desired prediction level.
          Levels increase from outermost to innermost grouping, with
          level 0 representing the population (fixed effects)
          predictions. Only one level can be specified. Defaults to the
          innermost level.

     ...: some methods for the generic may require additional
          arguments.

_V_a_l_u_e:

     a data frame with four columns representing, respectively, the
     values of the primary covariate, the groups (if 'object' does not
     have a grouping structure, all elements will be '1'), the
     predicted or observed values, and the type of value in the third
     column: the objects' names are used to classify the predicted
     values and 'original' is used for the observed values. The
     returned object inherits from classes 'comparePred' and 'augPred'.

_N_o_t_e:

     This function is generic; method functions can be written to
     handle specific classes of objects. Classes which already have
     methods for this function include: 'gls', 'lme', and 'lmList'.

_A_u_t_h_o_r(_s):

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

_S_e_e _A_l_s_o:

     'augPred', 'getGroups'

_E_x_a_m_p_l_e_s:

     fm1 <- lme(distance ~ age * Sex, data = Orthodont, random = ~ age)
     fm2 <- update(fm1, distance ~ age)
     comparePred(fm1, fm2, length.out = 2)