plot.nffGroupedData           package:nlme           R Documentation

Plot an nffGroupedData Object

Description:

     A Trellis dot-plot of the response by group is generated. If outer
     variables are specified, the combination of their levels are used
     to determine the panels of the Trellis display. The Trellis
     function 'dotplot' is used.

Usage:

     ## S3 method for class 'nffGroupedData':
     plot(x, outer, inner, innerGroups, xlab, ylab, strip, panel, key,
          grid, ...)

Arguments:

       x: an object inheriting from class 'nffGroupedData',
          representing a 'groupedData' object with a factor primary
          covariate and a single grouping level. 

   outer: an optional logical value or one-sided formula, indicating
          covariates that are outer to the grouping factor, which are
          used to determine the panels of the Trellis plot. If equal to
          'TRUE', 'attr(object, "outer")' is used to indicate the outer
          covariates. An outer covariate is invariant within the sets
          of rows defined by the grouping factor.  Ordering of the
          groups is done in such a way as to preserve adjacency of
          groups with the same value of the outer variables. Defaults
          to 'NULL', meaning that no outer covariates are to be used. 

   inner: an optional logical value or one-sided formula, indicating a
          covariate that is inner to the grouping factor, which is used
          to associate points within each panel of the Trellis plot. If
          equal to 'TRUE', 'attr(object, "inner")' is used to indicate
          the inner covariate. An inner covariate can change within the
          sets of rows defined by the grouping  factor. Defaults to
          'NULL', meaning that no inner covariate  is present.  

innerGroups: an optional one-sided formula specifying a factor to be
          used for grouping the levels of the 'inner' covariate.
          Different colors, or symbols, are used for each level of the
          'innerGroups' factor. Default is 'NULL', meaning that no
          'innerGroups' covariate is present. 

    xlab: an optional character string with the label for the
          horizontal axis. Default is the 'y' elements of 'attr(object,
          "labels")' and 'attr(object, "units")' pasted together. 

    ylab: an optional character string with the label for the vertical
          axis. Default is the grouping factor name. 

   strip: an optional function passed as the 'strip' argument to the
          'dotplot' function. Default is 'strip.default(..., style =
          1)' (see 'trellis.args'). 

   panel: an optional function used to generate the individual panels
          in the Trellis display, passed as the 'panel' argument to the
          'dotplot' function. 

     key: an optional logical function or function. If 'TRUE' and
          either 'inner' or 'innerGroups' are non-'NULL', a legend for
          the different 'inner' ('innerGroups') levels is  included at
          the top of the plot. If given as a function, it is passed as
          the 'key' argument to the 'dotplot' function. Default is
          'TRUE' is either 'inner' or 'innerGroups' are non-'NULL' and
          'FALSE' otherwise. 

    grid: this argument is included for consistency with the
          'plot.nfnGroupedData' method calling sequence. It is ignored
          in this method function.

     ...: optional arguments passed to the 'dotplot' function.

Value:

     a Trellis dot-plot of the response by group.

Author(s):

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

References:

     Bates, D.M. and Pinheiro, J.C. (1997), "Software Design for
     Longitudinal Data", in "Modelling Longitudinal and Spatially
     Correlated Data: Methods, Applications and Future Directions",
     T.G. Gregoire (ed.), Springer-Verlag, New York.

     Pinheiro, J.C. and Bates, D.M. (1997) "Future Directions in
     Mixed-Effects Software: Design of NLME 3.0" available at
     http://franz.stat.wisc.edu/pub/NLME.

See Also:

     'groupedData', 'dotplot'

Examples:

     plot(Machines)
     plot(Machines, inner = TRUE)

