HR                 package:SASmixed                 R Documentation

_H_e_a_r_t _r_a_t_e_s _o_f _p_a_t_i_e_n_t_s _o_n _d_i_f_f_e_r_e_n_t _d_r_u_g _t_r_e_a_t_m_e_n_t_s

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

     The 'HR' data frame has 120 rows and 5 columns of the heart rates
     of patients under one of three possible drug treatments.

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

     This data frame contains the following columns:

     _P_a_t_i_e_n_t an ordered factor indicating the patient.

     _D_r_u_g the drug treatment - a factor with levels 'a', 'b' and 'p'
          where 'p' represents the placebo.

     _b_a_s_e_H_R the patient's base heart rate

     _H_R the observed heart rate at different times in the experiment

     _T_i_m_e the time of the observation

_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
     3.5).

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

     str(HR)
     if (require("lattice", quietly = TRUE, character = TRUE)) {
       xyplot(HR ~ Time | Patient, HR, type = c("g", "p", "r"), aspect = "xy",
              index.cond = function(x, y) coef(lm(y ~ x))[1],
              ylab = "Heart rate (beats/min)")
     }
     if (require("lme4", quietly = TRUE, character = TRUE)) {
       options(contrasts = c(unordered = "contr.SAS", ordered = "contr.poly"))
       ## linear trend in time
       print(fm1HR <- lmer(HR ~ Time * Drug + baseHR + (Time|Patient), HR))  
       print(anova(fm1HR))
     ## Not run: 
     fm2HR <- update(fm1HR, weights = varPower(0.5)) # use power-of-mean variance
     summary(fm2HR)
     intervals(fm2HR)             # variance function does not seem significant
     anova(fm1HR, fm2HR)         # confirm with likelihood ratio
     ## End(Not run)
      print(fm3HR <- lmer(HR ~ Time + Drug + baseHR + (Time|Patient), HR))
      print(anova(fm3HR))
      ## remove Drug term
      print(fm4HR <- lmer(HR ~ Time + baseHR + (Time|Patient), HR))
      print(anova(fm4HR))
     }

