tire                package:multcomp                R Documentation

_T_i_r_e _W_e_a_r _D_a_t_a _S_e_t

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

     Operating costs per mile for two brands of tires; data set  taken
     from Westfall et al. (1999, p. 109). Confidence bands for 
     difference of regression functions.

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

     data(tire)

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

     This data frame contains the following variables

     _m_a_k_e Tire brand at 2 levels: 'A' and 'B'.

     _m_p_h Miles per Hour as predictor variable.

     _c_o_s_t Response variable: operating costs per mile.

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

     See Westfall et al. (1999, p. 109)

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

     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.

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

     data(tire)
     C <- c(0,1,-1,0,10,-10)
     for ( x in seq(15,70,5) ) { C <- rbind( C,c(0,1,-1,0,x,-x) ) }
     # numerate the contrasts
     rownames(C) <- paste("C", 1:nrow(C), sep="")

     # simultaneous confidence intervals for difference of regression functions
     summary(simint(cost ~ make*mph, data=tire,
                    cmatrix=C, eps=0.001))

