Cultivation             package:SASmixed             R Documentation

_B_a_c_t_e_r_i_a_l _i_n_n_o_c_u_l_a_t_i_o_n _a_p_p_l_i_e_d _t_o _g_r_a_s_s _c_u_l_t_i_v_a_r_s

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

     The `Cultivation' data frame has 24 rows and 4 columns of data
     from an experiment on the effect on dry weight yield of three
     bacterial inoculation treatments applied to two grass cultivars.

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

     This data frame contains the following columns:

     _B_l_o_c_k a factor with levels `1' to `4'

     _C_u_l_t the cultivar factor with levels `a' and `b'

     _I_n_o_c the innoculant factor with levels `con', `dea' and `liv'

     _d_r_y_w_t a numeric vector of dry weight yields

_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
     2.2(a)).

     Littel, R. C., Freund, R. J., and Spector, P. C. (1991), SAS
     System for Linear Models, Third Ed., SAS Institute.

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

     library(SASmixed)
     data(Cultivation)
     options(
       contrasts = c(unordered = "contr.SAS", ordered = "contr.poly"))
     names( Cultivation )
     formula( Cultivation )
     fm1Cult <- lme( drywt ~ Inoc * Cult, data = Cultivation, 
                     random = list( Block = ~ 1, Cult = ~ 1 ) )
     summary( fm1Cult )   # compare with Output 2.10, page 58
     VarCorr( fm1Cult )   
     anova( fm1Cult )
     fm2Cult <- update( fm1Cult, drywt ~ Inoc + Cult )
     anova( fm2Cult )
     fm3Cult <- update( fm1Cult, drywt ~ Inoc )
     anova( fm3Cult )
     summary( fm3Cult )
     VarCorr( fm3Cult )

