RatWeight | R Documentation |
Weight Gain in Rats Exposed to Thiouracil and Thyroxin
Description
The data are from a study of weight gain, where investigators randomly assigned 30 rats to three treatment groups: treatment 1 was a control (no additive); treatments 2 and 3 consisted of two different additives (thiouracil and thyroxin respectively) to the rats drinking water. Weight was measured at baseline (week 0) and at weeks 1, 2, 3, and 4. Due to an accident at the beginning of the study, data on 3 rats from the thyroxin group are unavailable.
Format
A data frame with 27 observations on the following 6 variables.
trt
a factor with levels
Control
Thiouracil
Thyroxin
wt0
Weight at Week 0 (baseline weight)
wt1
Weight at Week 1
wt2
Weight at Week 2
wt3
Weight at Week 3
wt4
Weight at Week 4
Details
The trt
factor comes supplied with contrasts comparing Control
to each of Thiouracil
and Thyroxin
.
Source
Originally from Box (1950), Table D (page 389), where the values for weeks 1-4 were recorded as the gain in weight for that week.
Fitzmaurice, G. M. and Laird, N. M. and Ware, J. H (2004). Applied Longitudinal Analysis, New York, NY: Wiley-Interscience. https://rdrr.io/rforge/ALA/.
References
Box, G.E.P. (1950). Problems in the analysis of growth and wear curves. Biometrics, 6, 362-389.
Friendly, Michael (2010). HE Plots for Repeated Measures Designs. Journal of Statistical Software, 37(4), 1-40. doi:10.18637/jss.v037.i04.
Examples
data(RatWeight)
contrasts(RatWeight$trt)
rat.mod <- lm(cbind(wt0, wt1, wt2, wt3, wt4) ~ trt, data=RatWeight)
rat.mod
idata <- data.frame(week = ordered(0:4))
car::Anova(rat.mod, idata=idata, idesign=~week, test="Roy")
# quick look at between group effects
pairs(rat.mod)
# between-S, baseline & week 4
heplot(rat.mod, col=c("red", "blue", "green3", "green3"),
variables=c(1,5),
hypotheses=c("trt1", "trt2"),
main="Rat weight data, Between-S effects")
# within-S
heplot(rat.mod, idata=idata, idesign=~week, iterm="week",
col=c("red", "blue", "green3"),
# hypotheses=c("trt1", "trt2"),
main="Rat weight data, Within-S effects")