

   LLiisstt ooff llmm OObbjjeeccttss wwiitthh aa CCoommmmoonn MMooddeell

        lmList(object, data, groups, level, na.action, pool)

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

     object: Either a linear formula object, with the response
             on the left of a `~' operator and the terms, sepa-
             rated by `+' operators, on the right or a
             `groupedData' object.  The method function
             `lmList.groupedData' is documented separately.

       data: a data frame in which to interpret the variables
             named in `formula' and `groups'.

     groups: an optional one-sided formula specifying the par-
             titioning of the data according to which different
             `lm' fits should be performed. Defaults to `get-
             GroupsFormula(data)', in which case `data' must
             inherit from class `groupedData'.

      level: an optional integer specifying the level of group-
             ing to be used when multiple nested levels of
             grouping are present.

   na.action: a function that indicates what should happen when
             the data contain `NA's.  The default action
             (`na.fail') causes `lmList' to print an error mes-
             sage and terminate if there are any incomplete
             observations.

       pool: an optional logical value that is preserved as an
             attribute of the returned value.  This will be
             used as the default for `pool' in calculations of
             standard deviations or standard errors for sum-
             maries.

   DDeessccrriippttiioonn::

        `Data' is partitioned according to the levels of the
        grouping factor defined in `groups', and individual
        `lm' fits are obtained for each `data' partition, using
        the model defined in `object'.

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

        a list of `lm' objects with as many components as the
        number of groups defined by `groups'. Generic functions
        such as `coef', `fixed.effects', `lme', `pairs',
        `plot', `predict', `random.effects', `summary', and
        `update' have methods that can be applied to an
        `lmList' object.

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

        `lm', `lme.lmList'.

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

        library(lme)
        data(Orthodont)
        fm1 <- lmList(distance ~ age, Orthodont, groups = ~Subject)

