finney71                 package:drc                 R Documentation

_E_x_a_m_p_l_e _f_r_o_m _F_i_n_n_e_y (_1_9_7_1)

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

     For each of six concentration of an insecticid the number of
     insects affected (out of the number of insects) was recorded.

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

     data(finney71)

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

     A data frame with 6 observations on the following 3 variables.

     '_d_o_s_e' a numeric vector

     '_t_o_t_a_l' a numeric vector

     '_a_f_f_e_c_t_e_d' a numeric vector

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

     Finney, D. J. (1971) _Probit Analysis_, Cambridge: Cambridge
     University Press.

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

     ## Model with ED50 as a parameter
     finney71.m1 <- drm(affected/total~dose, weights=total,
     data=finney71, fct=LL.2(), type="binomial")

     summary(finney71.m1)
     plot(finney71.m1, conLevel = 0.1, broken=TRUE, lwd = 2)

     ED(finney71.m1, c(10, 20, 50), ci="delta", reference="control")

     ## Model fitted with 'glm'
     #fitl.glm <- glm(cbind(affected, total-affected) ~ log(dose),
     #family=binomial(link = logit), data=finney71[finney71$dose != 0, ])
     #summary(fitl.glm)  # p-value almost agree for the b parameter
     #
     #xp <- dose.p(fitl.glm, p=c(0.50, 0.90, 0.95))  # from MASS
     #xp.ci <- xp + attr(xp, "SE") 
     #zp.est <- exp(cbind(xp.ci[,1],xp,xp.ci[,2]))
     #dimnames(zp.est)[[2]] <- c("zp.lcl","zp","zp.ucl")
     #zp.est  # not far from above results with 'ED'

     ## Model with log(ED50) as a parameter
     finney71.m2 <- drm(affected/total~dose, weights=total,
     data=finney71, fct=LL2.2(), type="binomial")

     ## Confidence intervals based on back-transformation
     ##  complete agreement with results based on 'glm'
     ED(finney71.m2, c(10, 20, 50), ci="fls", reference="control")

