

   CCoommppaarree PPrreeddiiccttiioonnss

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

   AArrgguummeennttss::

   object1,object2: fitted model objects, from which predic-
             tions can be extracted using the `predict' method.

    primary: an optional one-sided formula specifying the pri-
             mary covariate to be used to generate the aug-
             mented 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)'.

    maximum: an optional upper limit for the primary covariate.
             Defaults to `max(primary)'.

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

      level: an optional integer specifying the desired predic-
             tion 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 addi-
             tional arguments.

   DDeessccrriippttiioon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. `get-
        Groups(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 average (numeric covariates) or most fre-
        quent value (categorical covariates) are used to obtain
        the predicted values. The original observations are
        also included in the returned object.

   VVaalluuee::

        a data frame with four columns representing, respec-
        tively, 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 val-
        ues, and the type of value in the third column: the
        objects' names are used to classify the predicted val-
        ues and `original' is used for the observed values. The
        returned object inherits from classes `comparePred' and
        `augPred'.

   NNoottee::

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

   AAuutthhoorr((ss))::

        Jose Pinheiro and Douglas Bates

   SSeeee AAllssoo::

        `plot.comparePred', `augPred', `getGroups'

   EExxaammpplleess::

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

