plot.lmList               package:nlme               R Documentation

Plot an lmList Object

Description:

     Diagnostic plots for the linear model fits corresponding to the
     'x'  components are obtained. The 'form' argument gives
     considerable flexibility in the type of  plot specification. A
     conditioning expression (on the right side of a  '|' operator)
     always implies that different panels are used for  each level of
     the conditioning factor, according to a Trellis  display. If
     'form' is a one-sided formula, histograms of the  variable on the
     right hand side of the formula, before a '|'  operator, are
     displayed (the Trellis function 'histogram' is  used). If 'form'
     is two-sided and both its left and  right hand side variables are
     numeric, scatter plots are displayed  (the Trellis function
     'xyplot' is used). Finally, if 'form'  is two-sided and its left
     had side variable is a factor, box-plots of  the right hand side
     variable by the levels of the left hand side  variable are
     displayed (the Trellis function  'bwplot' is used).

Usage:

     ## S3 method for class 'lmList':
     plot(x, form, abline, id, idLabels, grid, ...)

Arguments:

       x: an object inheriting from class 'lmList', representing a list
          of 'lm' objects with a common model.

    form: an optional formula specifying the desired type of plot. Any
          variable present in the original data frame used to obtain
          'x' can be referenced. In addition, 'x' itself can be
          referenced in the formula using the symbol '"."'. Conditional
          expressions on the right of a '|' operator can be used to
          define separate panels in a Trellis display. Default is
          'resid(., type = "pool") ~ fitted(.) ', corresponding to a
          plot of the standardized residuals (using a pooled estimate
          for the residual standard error) versus fitted values. 

  abline: an optional numeric value, or numeric vector of length two.
          If given as a single value, a horizontal line will be added
          to the plot at that coordinate; else, if given as a vector,
          its values are used as the intercept and slope for a line
          added to the plot. If missing, no lines are added to the
          plot. 

      id: an optional numeric value, or one-sided formula. If given as
          a value, it is used as a significance level for a two-sided
          outlier test for the standardized residuals. Observations
          with absolute standardized residuals greater than the 1 -
          value/2 quantile of the standard normal distribution are
          identified in the plot using 'idLabels'. If given as a
          one-sided formula, its right hand side must evaluate to a 
          logical, integer, or character vector which is used to
          identify observations in the plot. If missing, no
          observations are identified. 

idLabels: an optional vector, or one-sided formula. If given as a
          vector, it is converted to character and used to label the
          observations identified according to 'id'. If given as a
          one-sided formula, its right hand side must evaluate to a
          vector which is converted to character and used to label the
          identified observations. Default is 'getGroups(x)'.  

    grid: an optional logical value indicating whether a grid should be
          added to plot. Default depends on the type of Trellis plot
          used: if 'xyplot' defaults to 'TRUE', else defaults to
          'FALSE'. 

     ...: optional arguments passed to the Trellis plot function.

Value:

     a diagnostic Trellis plot.

Author(s):

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

See Also:

     'lmList','predict.lm', 'xyplot', 'bwplot', 'histogram'

Examples:

     fm1 <- lmList(distance ~ age | Subject, Orthodont)
     # standardized residuals versus fitted values by gender
     plot(fm1, resid(., type = "pool") ~ fitted(.) | Sex, abline = 0, id = 0.05)
     # box-plots of residuals by Subject
     plot(fm1, Subject ~ resid(.))
     # observed versus fitted values by Subject
     plot(fm1, distance ~ fitted(.) | Subject, abline = c(0,1))

