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, correlation, weights, subset,
         method, na.action, control, model, x)

_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 level. The order of nesting will be
          assumed the same as the order of the elements in the list;
          (iii) a one-sided formula of the form `~x1+...+xn', or a
          `pdMat' object with a formula (i.e. a non-`NULL' value for
          `formula(object)'), or a list of such formulas or `pdMat'
          objects. In this case, the grouping structure formula will be
          derived from the data used to fit the linear mixed-effects
          model, which should inherit from class `groupedData'; (iv) a
          named list of formulas or `pdMat' objects as in (iii), with
          the grouping factors as names. The order of nesting will be
          assumed the same as the order of the order of the elements in
          the list; (v) an `reStruct' object. See the `pdMat-class'
          documentation for a description of the available `pdMat'
          classes. Defaults to a formula consisting of the right hand
          side of `formula'.

correlation: 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.

 weights: 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.

  subset: 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.

  method: 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"'.

na.action: 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.

 control: a list of control values for the estimation algorithm to
          replace the default values returned by the function
          `lmeControl'. Defaults to an empty list.

model, x: logicals.  If `TRUE' the corresponding components of the fit
          (the model frame, the model matrices) are returned.

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

     Many of the options are not yet implemented.

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

     An lme object.

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

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

