lmList                 package:lme4                 R Documentation

_L_i_s_t _o_f _l_m _O_b_j_e_c_t_s _w_i_t_h _a _C_o_m_m_o_n _M_o_d_e_l

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

     `Data' is partitioned according to the levels of the grouping
     factor `g' and individual `lm' fits are obtained for each `data'
     partition, using the model defined in `object'.

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

     lmList(formula, data, level, subset, na.action, pool)

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

 formula: For `lmList', a linear formula object of the form `y ~
          x1+...+xn | g'. In the formula object, `y' represents the
          response, `x1,...,xn' the covariates, and `g' the grouping
          factor specifying the partitioning of the data according to
          which different `lm' fits should be performed. The grouping
          factor `g' may be omitted from the formula, in which case the
          grouping structure will be obtained from `data', which must
          inherit from class `groupedData'. 

    data: a data frame in which to interpret the variables named in
          `object'.  

   level: an optional integer specifying the level of grouping to be
          used when  multiple nested levels of grouping are present. 

  subset: an optional expression indicating which subset of the rows of
          `data' 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.

na.action: a function that indicates what should happen when the data
          contain `NA's.  The default action (`na.fail') causes
          `lmList' to print an error message and terminate if there are
          any incomplete observations. 

    pool: an optional logical value that is preserved as an attribute
          of the returned value.  This will be used as the default for
          `pool' in calculations of standard deviations or standard
          errors for summaries. 

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

     an object of class lmList which is a list of `lm' objects with as
     many components as the number of groups defined by the grouping
     factor.

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

     `lm'

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

     data(Orthodont, package = 'nlme')
     fm1 <- lmList(distance ~ age | Subject, Orthodont)
     fm1

