fastR (version 0.10.3)

poison: Poison data

Description

The data give the survival times (in hours) in a 3 x 4 factorial experiment, the factors being (a) three poisons and (b) four treatments. Each combination of the two factors is used for four animals. The allocation to animals is completely randomized.

Format

A data frame with 48 observations on the following 3 variables.

• Poison type of poison (1, 2, or 3)

• Treatment manner of treatment (1, 2, 3, or 4)

• Time time until death (hours)

References

Box, G. E. P., and Cox, D. R. (1964). An analysis of transformations (with Discussion). J. R. Statist. Soc. B, 26, 211-252.

Aitkin, M. (1987). Modelling variance heterogeneity in normal regression using GLIM. Appl. Statist., 36, 332-339.

Smyth, G. K., and Verbyla, A. P. (1999). Adjusted likelihood methods for modelling dispersion in generalized linear models. Environmetrics 10, 696-709. http://www.statsci.org/smyth/pubs/ties98tr.html.

Examples

# NOT RUN {
data(poison)
poison.lm <- lm(Time~factor(Poison) * factor(Treatment), data=poison) 
xplot(poison.lm,w=c(4,2))
anova(poison.lm)
# improved fit using a transformation
poison.lm2 <- lm(1/Time~factor(Poison) * factor(Treatment), data=poison) 
xplot(poison.lm2,w=c(4,2))
anova(poison.lm)

# }