summary.lme               package:nlme               R Documentation

Summarize an lme Object

Description:

     Additional information about the linear mixed-effects fit
     represented by 'object' is extracted and included as components of
     'object'. The returned object is suitable for printing with the
     'print.summary.lme' method.

Usage:

     ## S3 method for class 'lme':
     summary(object, adjustSigma, verbose, ...)

Arguments:

  object: an object inheriting from class 'lme', representing a fitted
          linear mixed-effects model.

adjustSigma: an optional logical value. If 'TRUE' and the estimation
          method used to obtain 'object' was maximum likelihood, the
          residual standard error is multiplied by sqrt(nobs/(nobs -
          npar)), converting it to a REML-like estimate. This argument
          is only used when a single fitted object is passed to the
          function. Default is 'TRUE'.

 verbose: an optional logical value used to control the amount of
          output in the 'print.summary.lme' method. Defaults to
          'FALSE'.

     ...: some methods for this generic require additional arguments. 
          None are used in this method.

Value:

     an object inheriting from class 'summary.lme' with all components
     included in 'object' (see 'lmeObject' for a full description of
     the components) plus the following components: 

corFixed: approximate correlation matrix for the fixed effects
          estimates 

  tTable: a data frame with columns 'Value', 'Std. Error', 'DF',
          't-value', and 'p-value' representing respectively the fixed
          effects estimates, their approximate standard errors, the
          denominator degrees of freedom, the ratios between the
          estimates and their standard errors,  and the associated
          p-value from a t distribution. Rows correspond to the
          different fixed effects.

residuals: if more than five observations are used in the 'lme' fit, a
          vector with the minimum, first quartile, median, third
          quartile, and maximum of the innermost grouping level
          residuals distribution; else the innermost grouping level
          residuals.

     AIC: the Akaike Information Criterion corresponding to 'object'.

     BIC: the Bayesian Information Criterion corresponding to 'object'.

Author(s):

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

See Also:

     'AIC', 'BIC', 'lme', 'print.summary.lme'

Examples:

     fm1 <- lme(distance ~ age, Orthodont, random = ~ age | Subject)
     summary(fm1)

