Weights               package:SASmixed               R Documentation

_D_a_t_a _f_r_o_m _a _w_e_i_g_h_t-_l_i_f_t_i_n_g _p_r_o_g_r_a_m

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

     The 'Weights' data frame has 399 rows and 5 columns.

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

     This data frame contains the following columns:

     _s_t_r_e_n_g_t_h a numeric vector

     _S_u_b_j_e_c_t a factor with levels '1' to '21'

     _P_r_o_g_r_a_m a factor with levels 'CONT' (continuous repetitions and
          weights), 'RI' (repetitions increasing) and 'WI' (weights
          increasing)

     _S_u_b_j an ordered factor indicating the subject on which the
          measurement is made

     _T_i_m_e a numeric vector indicating the time of the measurement

_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
     3.2(a)).

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

     str(Weights)
     if (require("lme4", quietly = TRUE, character = TRUE)) {
       options(contrasts = c(unordered = "contr.SAS", ordered = "contr.poly"))
       ## compare with output 3.1, p. 91
       print(fm1Weight <- lmer(strength ~ Program * Time + (1|Subj), Weights))
       print(anova(fm1Weight))
       print(fm2Weight <- lmer(strength ~ Program * Time + (Time|Subj), Weights))
       print(anova(fm1Weight, fm2Weight))
     ## Not run: 
     intervals(fm2Weight)
     fm3Weight <- update(fm2Weight, correlation = corAR1())
     anova(fm2Weight, fm3Weight)
     fm4Weight <- update(fm3Weight, strength ~ Program * (Time + I(Time^2)),
                         random = ~Time|Subj)
     summary(fm4Weight)
     anova(fm4Weight)
     intervals(fm4Weight)
     ## End(Not run)
     }

