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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.

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).

1 |

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

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.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | ```
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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