Bartlett | R Documentation |
In an experiment to investigate the effect of cutting length (two levels) and planting time (two levels) on the survival of plum root cuttings, 240 cuttings were planted for each of the 2 x 2 combinations of these factors, and their survival was later recorded.
Bartlett (1935) used these data to illustrate a method for testing for no three-way interaction in a contingency table.
data(Bartlett)
A 3-dimensional array resulting from cross-tabulating 3 variables for 960 observations. The variable names and their levels are:
No | Name | Levels |
1 | Alive | "Alive", "Dead" |
2 | Time | "Now", "Spring" |
3 | Length | "Long", "Short" |
Hand, D. and Daly, F. and Lunn, A. D.and McConway, K. J. and Ostrowski, E. (1994). A Handbook of Small Data Sets. London: Chapman & Hall, p. 15, # 19.
Bartlett, M. S. (1935). Contingency Table Interactions Journal of the Royal Statistical Society, Supplement, 1935, 2, 248-252.
data(Bartlett)
# measures of association
assocstats(Bartlett)
oddsratio(Bartlett)
# Test models
## Independence
MASS::loglm(formula = ~Alive + Time + Length, data = Bartlett)
## No three-way association
MASS::loglm(formula = ~(Alive + Time + Length)^2, data = Bartlett)
# Use woolf_test() for a formal test of homogeneity of odds ratios
vcd::woolf_test(Bartlett)
# Plots
fourfold(Bartlett, mfrow=c(1,2))
mosaic(Bartlett, shade=TRUE)
pairs(Bartlett, gp=shading_Friendly)
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