Mississippi             package:SASmixed             R Documentation

_N_i_t_r_o_g_e_n _c_o_n_c_e_n_t_r_a_t_i_o_n_s _i_n _t_h_e _M_i_s_s_i_s_s_i_p_p_i _R_i_v_e_r

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

     The 'Mississippi' data frame has 37 rows and 3 columns.

_F_o_r_m_a_t:

     This data frame contains the following columns:

     _i_n_f_l_u_e_n_t an ordered factor with levels '3' < '5' < '2' < '1' < '4'
          < '6'

     _y a numeric vector

     _T_y_p_e a factor with levels '1'  '2'  '3' 

_S_o_u_r_c_e:

     Littel, R. C., Milliken, G. A., Stroup, W. W., and Wolfinger, R.
     D. (1996), _SAS System for Mixed Models_, SAS Institute (Data Set
     4.2).

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

     str(Mississippi)
     if (require("lattice", quietly = TRUE, character = TRUE)) {
       dotplot(drop(influent:Type) ~ y, groups = Type, Mississippi)
     } 
     if (require("lme4", quietly = TRUE, character = TRUE)) {
       options(contrasts = c(unordered = "contr.SAS", ordered = "contr.poly"))
       ## compare with output 4.1, p. 142
       print(fm1Miss <- lmer(y ~ 1 + (1|influent), Mississippi))
       ## compare with output 4.2, p. 143
       print(fm1MLMiss <- update(fm1Miss, method = "ML"))
       ## BLUP's of random effects on p. 142
       ranef(fm1Miss)            
       ## BLUP's of random effects on p. 144
       print(ranef(fm1MLMiss))
     #intervals(fm1Miss)       # interval estimates of variance components
       ## compare to output 4.8 and 4.9, pp. 150-152
       print(fm2Miss <- lmer(y ~ Type+(1|influent), Mississippi, method = "REML"))
       print(anova(fm2Miss))
     }

