esoph

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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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Plot

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Regression

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Attachment Size
dataset-74618.csv 2.58 KB
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Documentation

Smoking, Alcohol and (O)esophageal Cancer

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)
All Public Datasets File Size
Test 394 bytes
Q1 332 bytes
prova_Correlatio 593 bytes
profva
test 332 bytes
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