lme-class                package:lme4                R Documentation

_C_l_a_s_s "_l_m_e"

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

     A linear mixed-effects model.

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     Objects can be created by calls of the form `new("lme", ...)'.

_S_l_o_t_s:

     `_r_e_S_t_r_u_c_t': Object of class `"reStruct"', the random-effects
          structure for the model.

     `_f_r_a_m_e': Object of class `"data.frame"', the model.frame used to
          fit the model.

     `_n_a._a_c_t_i_o_n': Object of class `"ANY"', the `na.action' argument
          used when creating the `model.frame'.

     `_f_i_t_t_e_d': Object of class `"numeric"', the current fitted values.

     `_c_a_l_l': Object of class `"call"', the function call used to create
          the object.

_E_x_t_e_n_d_s:

     Class `"lme"', directly.

_M_e_t_h_o_d_s:

     _V_a_r_C_o_r_r `signature(x = "lme")': extract variance and correlation
          components.

     _a_n_o_v_a `signature(object = "lme")': calculate analysis of variance
          tables for linear mixed effects models.

     _c_o_e_f `signature(object = "lme")': extract the random effects
          parameters for the model.

     _f_i_t_t_e_d `signature(object = "lme")': extract the fitted values.

     _f_i_x_e_f `signature(object = "lme")': extract the fixed effects
          parameters.

     _f_o_r_m_u_l_a `signature(x = "lme")': extract the fixed effects formula.

     _g_e_t_R_e_s_p_o_n_s_e `signature(object = "lme")': extract the response.

     _i_n_t_e_r_v_a_l_s `signature(object = "lme")': calculate confidence
          intervals.

     _l_o_g_L_i_k `signature(object = "lme")': calculate the log-likelihood
          or log-restricted-likelihood for the model

     _p_l_o_t `signature(x = "lme")': plot the fitted model.

     _r_a_n_e_f `signature(object = "lme")': calculate the random-effects
          coefficients

     _r_e_s_i_d_u_a_l_s `signature(object = "lme")': calculate the residuals
          from the model fit.

     _s_h_o_w `signature(object = "lme")': show the object.

     _s_u_m_m_a_r_y `signature(object = "lme")': summarize the object.

     _u_p_d_a_t_e `signature(object = "lme")': update the model fit.

_A_u_t_h_o_r(_s):

     Saikat DebRoy saikat@stat.wisc.edu and Douglas Bates
     bates@stat.wisc.edu

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

     library(lme4)
     data(bdf, package = "nlme")
     # This returns an object of class lme
     fm <- lme(langPOST ~ IQ.ver.cen + avg.IQ.ver.cen, data = bdf,
               random = ~ IQ.ver.cen | schoolNR)
     fm

