etmotc                  package:drc                  R Documentation

_E_f_f_e_c_t _o_f _e_r_y_t_h_r_o_m_y_c_i_n _o_n _m_i_x_e_d _s_e_w_a_g_e _m_i_c_r_o_o_r_g_a_n_i_s_m_s

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

     Relative growth rate in biomass of mixed sewage microorganisms
     (per hour) as a function of increasing concentrations of the
     antibiotic erythromycin (mg/l).

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

     data(etmotc)

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

     A data frame with 57 observations on the following 4 variables.

     '_c_e_l_l' a numeric vector

     '_d_o_s_e_1' a numeric vector

     '_p_c_t_1' a numeric vector

     '_r_g_r_1' a numeric vector

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

     Data stem from an experiment investigating the effect of
     pharmaceuticals, that are used in human and veterinary medicine
     and that are being released into the aquatic environment through
     waste water or through manure used for fertilising agricultural
     land. The experiment constitutes a typical dose-response
     situation. The dose is concentration of the antibiotic
     erythromycin (mg/l), which is an antibiotic that can be used by
     persons or animals showing allergy to penicillin, and the measured
     response is the relative growth rate in biomass of mixed sewage
     microorganisms (per hour), measured as turbidity two hours after
     exposure by means of a spectrophotometer. The experiment was
     designed in such a way that eight replicates were assigned to the
     control (dose 0), but no replicates were assigned to the 7
     non-zero doses. Further details are found in Christensen et al
     (2006).

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

     Christensen, A. M. and Ingerslev, F. and Baun, A. 2006 
     Ecotoxicity of mixtures of antibiotics used in aquacultures. 
     _Environmental Toxicology and Chemistry_, *25*, 2208-2215.

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

     etmotc.m1<-drm(rgr1~dose1, data=etmotc[1:15,], fct=LL.4())
     plot(etmotc.m1)
     modelFit(etmotc.m1)
     summary(etmotc.m1)

     etmotc.m2<-drm(rgr1~dose1, data=etmotc[1:15,], fct=W2.4())
     plot(etmotc.m2, add = TRUE)
     modelFit(etmotc.m2)
     summary(etmotc.m2)

     etmotc.m3<-drm(rgr1~dose1, data=etmotc[1:15,], fct=W2.3())
     plot(etmotc.m3, add = TRUE)
     modelFit(etmotc.m3)
     summary(etmotc.m3)

