

   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, level, na.action, pool)

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

     object: either a linear formula object of the form `y ~
             x1+...+xn | g' or a `groupedData' object. In the
             formula object, `y' represents the response,
             `x1,...,xn' the covariates, and `g' the grouping
             factor specifying the partitioning of the data
             according to which different `lm' fits should be
             performed. The grouping factor `g' may be omitted
             from the formula, in which case the grouping
             structure will be obtained from `data', which must
             inherit from class `groupedData'. The method func-
             tion `lmList.groupedData' is documented sepa-
             rately.

       data: a data frame in which to interpret the variables
             named in `object'.

      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 `g' 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 the grouping factor.
        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 | Subject, Orthodont)

