lme                   package:lme4                   R Documentation

_F_i_t _l_i_n_e_a_r _m_i_x_e_d-_e_f_f_e_c_t_s _m_o_d_e_l_s

_D_e_s_c_r_i_p_t_i_o_n:

     This generic function fits a linear mixed-effects model in the
     formulation described in Laird and Ware (1982) but allowing for
     nested random effects. The within-group errors are allowed to be
     correlated and/or have unequal variances.

_U_s_a_g_e:

     lme(formula, data, random, ...)

_A_r_g_u_m_e_n_t_s:

 formula: a two-sided linear formula object describing the
          fixed-effects part of the model, with the response on the
          left of a '~' operator and the terms, separated by '+'
          operators, on the right.

    data: an optional data frame containing the variables named in
          'formula', 'random', 'correlation', 'weights', and 'subset'. 
          By default the variables are taken from the environment from
          which 'lme' is called.

  random: optionally, any of the following: (i) a one-sided formula of
          the form '~x1+...+xn | g1/.../gm', with 'x1+...+xn'
          specifying the model for the random effects and 'g1/.../gm'
          the grouping structure ('m' may be equal to 1, in which case
          no '/' is required). The random effects formula will be
          repeated for all levels of grouping, in the case of multiple
          levels of grouping; (ii) a list of one-sided formulas of the
          form '~x1+...+xn | g', with possibly different random effects
          models for each grouping factor; or (iii) a named list of
          formulas.

     ...: Optional arguments for methods.  Currently none are used.

_D_e_t_a_i_l_s:

     Additional standard arguments to model-fitting functions can be
     passed to 'lme'.

     _c_o_r_r_e_l_a_t_i_o_n an optional 'corStruct' object describing the
          within-group correlation structure. See the documentation of
          'corClasses' for a description of the available 'corStruct'
          classes. Defaults to 'NULL', corresponding to no within-group
          correlations. 

     _w_e_i_g_h_t_s an optional 'varFunc' object or one-sided formula
          describing the within-group heteroscedasticity structure. If
          given as a formula, it is used as the argument to 'varFixed',
          corresponding to fixed variance weights. See the
          documentation on 'varClasses' for a description of the
          available 'varFunc' classes. Defaults to 'NULL',
          corresponding to homocesdatic within-group errors. 

     _s_u_b_s_e_t an optional expression indicating the subset of the rows of
          'data' that should be used in the fit. This can be a logical
          vector, or a numeric vector indicating which observation
          numbers are to be included, or a  character  vector of the
          row names to be included.  All observations are included by
          default.

     _m_e_t_h_o_d a character string.  If '"REML"' the model is fit by
          maximizing the restricted log-likelihood.  If '"ML"' the
          log-likelihood is maximized.  Defaults to '"REML"'.

     _n_a._a_c_t_i_o_n a function that indicates what should happen when the
          data contain 'NA's.  The default action ('na.fail') causes
          'lme' to print an error message and terminate if there are
          any incomplete observations.

     _c_o_n_t_r_o_l a list of control values for the estimation algorithm to
          replace the default values returned by the function
          'lmeControl'. Defaults to an empty list.

     _m_o_d_e_l, _x logicals.  If 'TRUE' the corresponding components of the
          fit (the model frame, the model matrices) are returned.

_V_a_l_u_e:

     An 'lme-class{lme}' object.

_S_e_e _A_l_s_o:

     'lme-class', 'lm'

_E_x_a_m_p_l_e_s:

     data(bdf)
     fm <- lme(langPOST ~ IQ.ver.cen + avg.IQ.ver.cen, data = bdf,
               random = ~ IQ.ver.cen | schoolNR)
     summary(fm)

