fitted.lme               package:nlme               R Documentation

_E_x_t_r_a_c_t _l_m_e _F_i_t_t_e_d _V_a_l_u_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     The fitted values at level i are obtained by adding together the
     population fitted values (based only on the fixed effects
     estimates) and the estimated contributions of the random effects
     to the fitted values at grouping levels less or equal to i. The
     resulting values estimate the best linear unbiased predictions
     (BLUPs) at level i.

_U_s_a_g_e:

     ## S3 method for class 'lme':
     fitted(object, level, asList, ...)

_A_r_g_u_m_e_n_t_s:

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

   level: an optional integer vector giving the level(s) of grouping to
          be used in extracting the fitted values from 'object'. Level
          values increase from outermost to innermost grouping, with
          level zero corresponding to the population fitted values.
          Defaults to the highest or innermost level of grouping.

  asList: an optional logical value. If 'TRUE' and a single value is
          given in 'level', the returned object is a list with the
          fitted values split by groups; else the returned value is
          either a vector or a data frame, according to the length of
          'level'. Defaults to 'FALSE'.

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

_V_a_l_u_e:

     If a single level of grouping is specified in 'level', the
     returned value is either a list with the fitted values split by
     groups ('asList = TRUE') or a vector with the fitted values
     ('asList = FALSE'); else, when multiple grouping levels are
     specified in 'level', the returned object is a data frame with
     columns given by the fitted values at different levels and the
     grouping factors.  For a vector or data frame result the
     'napredict' method is applied.

_A_u_t_h_o_r(_s):

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

_R_e_f_e_r_e_n_c_e_s:

     Bates, D.M. and Pinheiro, J.C. (1998) "Computational methods for
     multilevel models" available in PostScript or PDF formats at
     http://nlme.stat.wisc.edu/pub/NLME/

     Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models in S
     and S-PLUS", Springer, esp. pp. 235, 397.

_S_e_e _A_l_s_o:

     'lme', 'residuals.lme'

_E_x_a_m_p_l_e_s:

     fm1 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1)
     fitted(fm1, level = 0:1)