R Dataset / Package datasets / esoph

How To Create a Barplot

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How To Create a Stacked Barplot

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How To Create a Pie Chart

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How To Compute the Mean

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How To Create a Plot

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How to Compute the Median

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Boxplot

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Correlation Coefficient

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Cumulative Frequency Histogram

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Dotplot

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Hollow Histogram

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Numerical Summaries

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Pie Chart

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Plot

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Regression

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Visual Summaries

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Embed
<iframe src="https://embed.picostat.com/r-dataset-package-datasets-esoph.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-87569.csv 2.58 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Dataset Help

On this Picostat.com statistics page, you will find information about the esoph data set which pertains to Smoking, Alcohol and (O)esophageal Cancer. The esoph data set is found in the datasets R package. You can load the esoph data set in R by issuing the following command at the console data("esoph"). This will load the data into a variable called esoph. If R says the esoph data set is not found, you can try installing the package by issuing this command install.packages("datasets") 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 esoph R data set. The size of this file is about 2,645 bytes.

Documentation

Smoking, Alcohol and (O)esophageal Cancer

Description

Data from a case-control study of (o)esophageal cancer in Ille-et-Vilaine, France.

Usage

esoph

Format

A data frame with records for 88 age/alcohol/tobacco combinations.

[,1] "agegp" Age group 1 25--34 years
2 35--44
3 45--54
4 55--64
5 65--74
6 75+
[,2] "alcgp" Alcohol consumption 1 0--39 gm/day
2 40--79
3 80--119
4 120+
[,3] "tobgp" Tobacco consumption 1 0-- 9 gm/day
2 10--19
3 20--29
4 30+
[,4] "ncases" Number of cases
[,5] "ncontrols" Number of controls

Author(s)

Thomas Lumley

Source

Breslow, N. E. and Day, N. E. (1980) Statistical Methods in Cancer Research. Volume 1: The Analysis of Case-Control Studies. IARC Lyon / Oxford University Press.

Examples

require(stats)
require(graphics) # for mosaicplot
summary(esoph)
## effects of alcohol, tobacco and interaction, age-adjusted
model1 <- glm(cbind(ncases, ncontrols) ~ agegp + tobgp * alcgp,
              data = esoph, family = binomial())
anova(model1)
## Try a linear effect of alcohol and tobacco
model2 <- glm(cbind(ncases, ncontrols) ~ agegp + unclass(tobgp)
                                         + unclass(alcgp),
              data = esoph, family = binomial())
summary(model2)
## Re-arrange data for a mosaic plot
ttt <- table(esoph$agegp, esoph$alcgp, esoph$tobgp)
o <- with(esoph, order(tobgp, alcgp, agegp))
ttt[ttt == 1] <- esoph$ncases[o]
tt1 <- table(esoph$agegp, esoph$alcgp, esoph$tobgp)
tt1[tt1 == 1] <- esoph$ncontrols[o]
tt <- array(c(ttt, tt1), c(dim(ttt),2),
            c(dimnames(ttt), list(c("Cancer", "control"))))
mosaicplot(tt, main = "esoph data set", color = TRUE)
--

Dataset imported from https://www.r-project.org.

R Output Date
Picostat Output - Dotplot Jun 10, 2020