Learn R Programming

vcd (version 1.4-11)

CoalMiners: Breathlessness and Wheeze in Coal Miners

Description

Data from Ashford & Sowden (1970) given by Agresti (1990) on the association between two pulmonary conditions, breathlessness and wheeze, in a large sample of coal miners who were smokers with no radiological evidence of pneumoconlosis, aged between 20--64 when examined. This data is frequently used as an example of fitting models for bivariate, binary responses.

Usage

data("CoalMiners")

Arguments

Format

A 3-dimensional table of size 2 x 2 x 9 resulting from cross-tabulating variables for 18,282 coal miners. The variables and their levels are as follows:

NoNameLevels
1BreathlessnessB, NoB
2WheezeW, NoW
3Age20-24, 25-29, 30-34, ..., 60-64

Details

In an earlier version of this data set, the first group, aged 20-24, was inadvertently omitted from this data table and the breathlessness variable was called wheeze and vice versa.

References

A. Agresti (1990), Categorical Data Analysis. Wiley-Interscience, New York, Table 7.11, p. 237

J. R. Ashford and R. D. Sowdon (1970), Multivariate probit analysis, Biometrics, 26, 535--546.

M. Friendly (2000), Visualizing Categorical Data. SAS Institute, Cary, NC.

Examples

Run this code
data("CoalMiners")

ftable(CoalMiners, row.vars = 3)

## Fourfold display, both margins equated
fourfold(CoalMiners[,,2:9], mfcol = c(2,4))

## Fourfold display, strata equated
fourfold(CoalMiners[,,2:9], std = "ind.max", mfcol = c(2,4))


## Log Odds Ratio Plot
lor_CM <- loddsratio(CoalMiners)
summary(lor_CM)
plot(lor_CM)
lor_CM_df <- as.data.frame(lor_CM)

# fit linear models using WLS
age <- seq(20, 60, by = 5)
lmod <- lm(LOR ~ age, weights = 1 / ASE^2, data = lor_CM_df)
grid.lines(age, fitted(lmod), gp = gpar(col = "blue"))
qmod <- lm(LOR ~ poly(age, 2), weights = 1 / ASE^2, data = lor_CM_df)
grid.lines(age, fitted(qmod), gp = gpar(col = "red"))

Run the code above in your browser using DataLab