cell {bootstrap}

Cell Survival data

Description

Data on cell survival under different radiation doses.

Usage

data(cell)

Format

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

dose

a numeric vector, unit rads/100

log.surv

a numeric vector, (natural) logarithm of proportion

Details

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 = \mbox{E}(y_i \vert z_i) = \beta_1 z_i

and the other predicting a quadratic regression,

\mu_i = \mbox{E}(y_i \vert z_i) = \beta_1 z_i+\beta_2 z_i^2

Hypothesis tests on \beta_2 is of interest.

Source

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

Examples

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))