# R Dataset / Package HistData / CushnyPeebles

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On this R-data statistics page, you will find information about the CushnyPeebles data set which pertains to Cushny-Peebles Data: Soporific Effects of Scopolamine Derivatives. The CushnyPeebles data set is found in the HistData R package. You can load the CushnyPeebles data set in R by issuing the following command at the console data("CushnyPeebles"). This will load the data into a variable called CushnyPeebles. If R says the CushnyPeebles data set is not found, you can try installing the package by issuing this command install.packages("HistData") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the CushnyPeebles R data set. The size of this file is about 224 bytes. ## Cushny-Peebles Data: Soporific Effects of Scopolamine Derivatives## DescriptionCushny and Peebles (1905) studied the effects of hydrobromides related to scopolamine and atropine in producing sleep. The sleep of mental patients was measured without hypnotic ( The drugs were given on alternate evenings, and the hours of sleep were compared with the intervening control night. Each of the drugs was tested in this manner a varying number of times in each subject. The average number of hours of sleep for each treatment is the response. Student (1908) used these data to illustrate the paired-sample t-test in small samples, testing the hypothesis that the mean difference between a given drug and the control condition was zero. This data set became well known when used by Fisher (1925). Both Student and Fisher had problems labeling the drugs correctly (see Senn & Richardson (1994)), and consequently came to wrong conclusions. But as well, the sample sizes (number of nights) for each mean differed widely, ranging from 3-9, and this was not taken into account in their analyses. To allow weighted analyses, the number of observations for each mean is contained in the data frame ## Usagedata(CushnyPeebles) data(CushnyPeeblesN) ## Format
`Control` -
a numeric vector: mean hours of sleep `L_hyoscyamine` -
a numeric vector: mean hours of sleep `L_hyoscine` -
a numeric vector: mean hours of sleep `D_hyoscine` -
a numeric vector: mean hours of sleep
`Control` -
a numeric vector: number of observations `L_hyoscyamine` -
a numeric vector: number of observations `L_hyoscine` -
a numeric vector: number of observations `DL_hyoscine` -
a numeric vector: number of observations
## DetailsThe last patient (11) has no ## SourceCushny, A. R., and Peebles, A. R. (1905), "The Action of Optical Isomers. II: Hyoscines," Senn, Stephen, Data from Cushny and Peebles, http://www.senns.demon.co.uk/Data/Cushny.xls ## ReferencesFisher, R. A. (1925), Student (1908), "The Probable Error of a Mean," Senn, S.J. and Richardson, W. (1994), "The first t-test", ## See Also
## Examplesdata(CushnyPeebles) # quick looks at the data plot(CushnyPeebles) boxplot(CushnyPeebles, ylab="Hours of Sleep", xlab="Treatment")########################## # Repeated measures MANOVA require(car)CPmod <- lm(cbind(Control, L_hyoscyamine, L_hyoscine, DL_hyoscine) ~ 1, data=CushnyPeebles)# Assign within-S factor and contrasts Treatment <- factor(colnames(CushnyPeebles), levels=colnames(CushnyPeebles)) contrasts(Treatment) <- matrix( c(-3, 1, 1, 1, 0,-2, 1, 1, 0, 0,-1, 1), ncol=3) colnames(contrasts(Treatment)) <- c("Control.Drug", "L.DL", "L_hy.DL_hy")Treats <- data.frame(Treatment) (CPaov <- Anova(CPmod, idata=Treats, idesign= ~Treatment)) summary(CPaov, univariate=FALSE)if (require(heplots)) { heplot(CPmod, idata=Treats, idesign= ~Treatment, iterm="Treatment", xlab="Control vs Drugs", ylab="L vs DL drug") pairs(CPmod, idata=Treats, idesign= ~Treatment, iterm="Treatment") }################################ # reshape to long format, add NsCPlong <- stack(CushnyPeebles)[,2:1] colnames(CPlong) <- c("treatment", "sleep") CPN <- stack(CushnyPeeblesN) CPlong <- data.frame(patient=rep(1:11,4), CPlong, n=CPN$values) str(CPlong) -- Dataset imported from https://www.r-project.org. |

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Attachment | Size |
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dataset-51664.csv | 224 bytes |