Dialyzer                package:nlme                R Documentation

_H_i_g_h-_F_l_u_x _H_e_m_o_d_i_a_l_y_z_e_r

_D_e_s_c_r_i_p_t_i_o_n:

     The 'Dialyzer' data frame has 140 rows and 5 columns.

_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 '10' < '8' < '2' < '6' < '3'
          < '5' < '9' < '7' < '1' < '4' < '17' < '20' < '11' < '12' <
          '16' < '13' < '14' < '18' < '15' < '19' giving the unique
          identifier for each subject

     _Q_B a factor with levels '200' and  '300' giving the bovine blood
          flow rate (dL/min).

     _p_r_e_s_s_u_r_e a numeric vector giving the transmembrane pressure
          (dmHg).

     _r_a_t_e the hemodialyzer ultrafiltration rate (mL/hr).

     _i_n_d_e_x index of observation within subject-1 through 7.

_D_e_t_a_i_l_s:

     Vonesh and Carter (1992) describe data measured on high-flux
     hemodialyzers to assess their _in vivo_ ultrafiltration
     characteristics. The ultrafiltration rates (in mL/hr) of 20
     high-flux dialyzers were measured at seven different transmembrane
     pressures (in dmHg). The _in vitro_ evaluation of the dialyzers
     used bovine blood at flow rates of either 200~dl/min or
     300~dl/min. The data, are also analyzed in Littell, Milliken,
     Stroup, and Wolfinger (1996).

_S_o_u_r_c_e:

     Pinheiro, J. C. and Bates, D. M. (2000), _Mixed-Effects Models in
     S and S-PLUS_, Springer, New York. (Appendix A.6)

     Vonesh, E. F. and Carter, R. L. (1992), Mixed-effects nonlinear
     regression for unbalanced repeated measures, _Biometrics_, *48*,
     1-18.

     Littell, R. C., Milliken, G. A., Stroup, W. W. and Wolfinger, R.
     D. (1996), _SAS System for Mixed Models_, SAS Institute, Cary, NC.

_E_x_a_m_p_l_e_s:

     data(Dialyzer)

