Theoph               package:datasets               R Documentation

_P_h_a_r_m_a_c_o_k_i_n_e_t_i_c_s _o_f _t_h_e_o_p_h_y_l_l_i_n_e

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

     The 'Theoph' data frame has 132 rows and 5 columns of data from an
     experiment on the pharmacokinetics of theophylline.

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

     Theoph

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

     This data frame contains the following columns:

     _S_u_b_j_e_c_t an ordered factor with levels '1', ..., '12' identifying
          the subject on whom the observation was made.  The ordering
          is by increasing maximum concentration of theophylline
          observed.

     _W_t weight of the subject (kg).

     _D_o_s_e dose of theophylline administered orally to the subject
          (mg/kg).

     _T_i_m_e time since drug administration when the sample was drawn
          (hr).

     _c_o_n_c theophylline concentration in the sample (mg/L).


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

     Boeckmann, Sheiner and Beal (1994) report data from a study by Dr.
     Robert Upton of the kinetics of the anti-asthmatic drug
     theophylline.  Twelve subjects were given oral doses of
     theophylline then serum concentrations were measured at 11 time
     points over the next 25 hours.

     These data are analyzed in Davidian and Giltinan (1995) and
     Pinheiro and Bates (2000) using a two-compartment open
     pharmacokinetic model, for which a self-starting model function,
     'SSfol', is available.

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

     Boeckmann, A. J., Sheiner, L. B. and Beal, S. L. (1994), _NONMEM
     Users Guide: Part V_, NONMEM Project Group, University of
     California, San Francisco.

     Davidian, M. and Giltinan, D. M. (1995) _Nonlinear Models for
     Repeated Measurement Data_, Chapman & Hall (section 5.5, p. 145
     and section 6.6, p. 176)

     Pinheiro, J. C. and Bates, D. M. (2000) _Mixed-effects Models in S
     and S-PLUS_, Springer (Appendix A.29)

_S_e_e _A_l_s_o:

     'SSfol'

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

     require(stats); require(graphics)
     coplot(conc ~ Time | Subject, data = Theoph, show.given = FALSE)
     Theoph.4 <- subset(Theoph, Subject == 4)
     fm1 <- nls(conc ~ SSfol(Dose, Time, lKe, lKa, lCl),
                data = Theoph.4)
     summary(fm1)
     plot(conc ~ Time, data = Theoph.4,
          xlab = "Time since drug administration (hr)",
          ylab = "Theophylline concentration (mg/L)",
          main = "Observed concentrations and fitted model",
          sub  = "Theophylline data - Subject 4 only",
          las = 1, col = 4)
     xvals <- seq(0, par("usr")[2], length.out = 55)
     lines(xvals, predict(fm1, newdata = list(Time = xvals)),
           col = 4)

