detergent              package:multcomp              R Documentation

_D_e_t_e_r_g_e_n_t _D_u_r_a_b_i_l_i_t_y _D_a_t_a _S_e_t

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

     Detergent durability in an incomplete two-way design.

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

     data("detergent")

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

     This data frame contains the following variables

     _d_e_t_e_r_g_e_n_t detergent, a factor at levels 'A', 'B',  'C', 'D', and
          'E'.

     _b_l_o_c_k block, a factor at levels 'B_1', ..., 'B_10'.

     _p_l_a_t_e_s response variable: number of plates washed before  the foam
          disappears.

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

     Plates were washed with five detergent varieties, in ten blocks. A
     complete design would have 50 combinations, here only three
     detergent varieties  in each block were applied in a balanced
     incomplete block design. Note that there are six observations
     taken at each detergent level.

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

     H. Scheffe (1959). _The Analysis of Variance_.  New York: John
     Wiley & Sons, page 189.

     P. H. Westfall, R. D. Tobias, D. Rom, R. D. Wolfinger, Y. Hochberg
     (1999). _Multiple Comparisons and Multiple Tests Using the SAS
     System_. Cary, NC: SAS Institute Inc., page 189.

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

       ### set up two-way ANOVA without interactions
       amod <- aov(plates ~ block + detergent, data = detergent)

       ### set up all-pair comparisons
       dht <- glht(amod, linfct = mcp(detergent = "Tukey"))

       ### see Westfall et al. (1999, p. 190)
       confint(dht)

       ### see Westfall et al. (1999, p. 192)
       summary(dht, test = univariate())
       summary(dht, test = adjusted("Shaffer"))
       summary(dht, test = adjusted("Westfall"))

