Headache | R Documentation |
A study was conducted investigating the effectiveness of different kinds of psychological treatment on the sensitivity of headache sufferers to noise, described in Hand and Taylor (1987), Study E.
A data frame with 98 observations on the following 6 variables.
type
Type of headache, a factor with levels Migrane
Tension
treatment
Treatment group, a factor with levels T1
T2
T3
Control
. See Details
u1
Noise level rated as Uncomfortable, initial measure
du1
Noise level rated as Definitely Uncomfortable, initial measure
u2
Noise level rated as Uncomfortable, final measure
du2
Noise level rated as Definitely Uncomfortable, final measure
In a pre-post design, 98 patients were first assessed for the volume of noise which they found uncomfortable (U) and definitely uncomfortable (DU). They were then given relaxation training, where they listened to the noise at the DU level and given instruction breathing techniques and the use of visual imagery to distract them from discomfort. One of four treatments was then applied, and all patients were reassessed for the noise volume they considered uncomfortable (U) and definitely uncomfortable (DU).
The treatments are described as follows:
T1
Listened again to the tone at their initial DU level, for the same amount of time they were able to tolerate it before.
T2
Same as T1, with one additional minute exposure
T3
Same as T2, but were explicitly instructed to use the relaxation techniques
Control
These subject experienced no further exposure to the noise tone until the final sensitivity measures were taken
Hand and Taylor described several substantive hypotheses related to the
differences among treatments. In the Headache
data frame, these have
been included as contrasts(Headache$treatment)
D. J. Hand and C. C. Taylor (1987). Multivariate analysis of variance and repeated measures: a practical approach for behavioural scientists London: Chapman and Hall. ISBN: 0412258005. Table E.1.
library(car)
data(Headache)
str(Headache)
# basic MLM, specifying between-S effects
headache.mod <- lm(cbind(u1, du1, u2, du2) ~ type * treatment, data=Headache)
##############################
## between-S tests
##############################
Anova(headache.mod, test="Roy")
# test each contrast separately
print(linearHypothesis(headache.mod, hypothesis="treatment1", test="Roy"), SSP=FALSE)
print(linearHypothesis(headache.mod, hypothesis="treatment2", test="Roy"), SSP=FALSE)
print(linearHypothesis(headache.mod, hypothesis="treatment3", test="Roy"), SSP=FALSE)
heplot(headache.mod, variables=c(1,3),
hypotheses=paste("treatment", 1:3, sep=""),
hyp.labels=c("extra.exp", "no.inst", "explicit.inst"),
xlab="u1: Initial sensitivity", ylab="u2: Final sensitivity",
main="Headache data: Unpleasant levels")
abline(0, 1, lty=5, col="gray")
heplot(headache.mod, variables=c(2,4),
hypotheses=paste("treatment", 1:3, sep=""),
xlab="du1: Initial sensitivity", ylab="du2: Final sensitivity",
main="Headache data: Definitely Unpleasant levels")
abline(0, 1, lty=5, col="gray")
pairs(headache.mod)
##############################
# between-S and within-S tests
##############################
idata = expand.grid(level=factor(c("U", "DU")), phase=factor(1:2))
Anova(headache.mod, idata=idata, idesign=~level*phase)
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