CoalMiners: Breathlessness and Wheeze in Coal Miners

In vcd: Visualizing Categorical Data

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")

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:

No	Name	Levels
1	Breathlessness	B, NoB
2	Wheeze	W, NoW
3	Age	20-24, 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.

Source

Michael Friendly (2000), Visualizing Categorical Data, pages 82–83, 319–322.

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

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"))

vcd documentation built on Feb. 16, 2023, 5:38 p.m.