ranef.lme                package:nlme                R Documentation

_E_x_t_r_a_c_t _l_m_e _R_a_n_d_o_m _E_f_f_e_c_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     The estimated random effects at level i are represented as a data
     frame with rows given by the different groups at that level and
     columns given by the random effects. If a single level of grouping
     is specified, the returned object is a data frame; else, the
     returned object is a list of such data frames. Optionally, the
     returned data frame(s) may be augmented with covariates summarized
     over groups.

_U_s_a_g_e:

     ## S3 method for class 'lme':
     ranef(object, augFrame, level, data, which, FUN,
           standard, omitGroupingFactor, subset, ...)

_A_r_g_u_m_e_n_t_s:

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

augFrame: an optional logical value. If 'TRUE', the returned data frame
          is augmented with variables defined in 'data'; else, if
          'FALSE', only the coefficients are returned. Defaults to
          'FALSE'.

   level: an optional vector of positive integers giving the levels of
          grouping to be used in extracting the random effects from an
          object with multiple nested grouping levels. Defaults to all
          levels of grouping.

    data: an optional data frame with the variables to be used for
          augmenting the returned data frame when 'augFrame = TRUE'.
          Defaults to the data frame used to fit 'object'.

   which: an optional positive integer vector specifying which columns
          of 'data' should be used in the augmentation of the returned
          data frame. Defaults to all columns in 'data'.

     FUN: an optional summary function or a list of summary functions
          to be applied to group-varying variables, when collapsing
          'data' by groups.  Group-invariant variables are always
          summarized by the unique value that they assume within that
          group. If 'FUN' is a single function it will be applied to
          each non-invariant variable by group to produce the summary
          for that variable.  If 'FUN' is a list of functions, the
          names in the list should designate classes of variables in
          the frame such as 'ordered', 'factor', or 'numeric'.  The
          indicated function will be applied to any group-varying
          variables of that class.  The default functions to be used
          are 'mean' for numeric factors, and 'Mode' for both 'factor'
          and 'ordered'.  The 'Mode' function, defined internally in
          'gsummary', returns the modal or most popular value of the
          variable.  It is different from the 'mode' function that
          returns the S-language mode of the variable.

standard: an optional logical value indicating whether the estimated
          random effects should be "standardized" (i.e. divided by the
          corresponding estimated standard error). Defaults to 'FALSE'.

omitGroupingFactor: an optional logical value.  When 'TRUE' the
          grouping factor itself will be omitted from the group-wise
          summary of 'data' but the levels of the grouping factor will
          continue to be used as the row names for the returned data
          frame. Defaults to 'FALSE'.

  subset: an optional expression indicating for which rows the random
          effects should be extracted.

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

_V_a_l_u_e:

     a data frame, or list of data frames, with the estimated  random
     effects at the grouping level(s) specified in 'level' and,
     optionally, other covariates  summarized over groups. The returned
     object inherits from classes 'random.effects.lme' and
     'data.frame'.

_A_u_t_h_o_r(_s):

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

_S_e_e _A_l_s_o:

     'lme',  'coef.lme', 'plot.ranef.lme', 'gsummary'

_E_x_a_m_p_l_e_s:

     data(Orthodont)
     fm1 <- lme(distance ~ age, Orthodont, random = ~ age | Subject)
     ranef(fm1)
     random.effects(fm1)             # same as above
     random.effects(fm1, augFrame = TRUE)

