cell                package:bootstrap                R Documentation

_C_e_l_l _S_u_r_v_i_v_a_l _d_a_t_a

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

     Data on cell survival under different radiation  doses.

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

     data(cell)

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

     A data frame with 14 observations on the following 2 variables.

     _d_o_s_e a numeric vector, unit rads/100 

     _l_o_g._s_u_r_v a numeric vector, (natural) logarithm of proportion

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

     There are regression situations where the covariates are more
     naturally  considered  fixed rather than random. This cell
     survival data are an example. A  radiologist has run an experiment
     involving 14 bacterial plates. The plates where exposed to 
     different  doses of radiation, and the proportion of surviving
     cells measured.  Greater doses lead to smaller survival
     proportions, as would be expected. The investigator  expressed
     some  doubt as to the validity of observation 13. 

     So there is some interest as to the influence of observation 13 on
     the  conclusions.

     Two different theoretical models as to radiation damage were
     available,  one predicting  a linear regresion, 

                  {mu_i = E(y_i | z_i) = beta_1 z_i}

     and the other predicting a quadratic regression,

          {mu_i = E(y_i | z_i) = beta_1 z_i + beta_2 z_i^2}

     Hypothesis tests on beta_2 is of interest.

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

     Efron, B. and Tibshirani, R. (1993) An Introduction to the
     Bootstrap. Chapman and Hall, New York, London.

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

     plot(cell[,2:1],pch=c(rep(1,12),17,1),
                     col=c(rep("black",12),"red", "black"),
                     cex=c(rep(1,12), 2, 1))

