byssinosis


  The dataset contains the number of workers in a survey
of the US cotton industry suffering  and not suffering
 from the lung disease byssinosis, together with the
values of five cross-classifying categorical explanatory variables:
the  race,  sex and smoking habit of the worker,
the length of employment in three categories, and the
dustiness of the workplace in three categories.


datasets

This package accompanies Aitkin et al, Statistical
Modelling in R, OUP, 2009. The package contains some functions
and datasets used in the text.

Ross Darnell

SMIR

Companion to Statistical Modelling in R

byssinosis function

A data.frame of 72 obs. of 7 variables:
  <table><tr><td>
    [,1] </td>
<td> dust </td>
</tr><tr><td> Factor w/ 3 levels "most","less"</td>
<td>
    [,2] </td>
</tr><tr><td> race</td>
<td>  Factor w/ 2 levels "white","non-white"</td>
</tr><tr><td>
    [,3] </td>
<td> sex </td>
</tr><tr><td>  Factor w/ 2 levels "male","female"</td>
<td>
    [,4]</td>
</tr><tr><td> smok </td>
<td> Factor w/ 2 levels "smoker","non"</td>
</tr><tr><td>
    [,5] </td>
<td> emp </td>
</tr><tr><td> Factor w/ 3 levels "<10","10-20",...< td="">
<td>
    [,6] </td>
</10","10-20",...<></td></tr><tr><td> yes </td>
<td> int, Number of workers who suffered byssinosis</td>
</tr></table>

Format

Higgins, J.E. and Koch, G.G. (1977), "Variable selection and generalized chi-square
                  analysis of categorical data to a large
                  cross-sectional occupational health survey",
		  <em>Int. Statist. Rev.</em>, <b>45</b>, 51--62.

byssinosis: Byssinosis in the cotton industry

Description

Usage

Arguments

Format

Source

[,1]	dust
Factor w/ 3 levels "most","less"	[,2]
race	Factor w/ 2 levels "white","non-white"
[,3]	sex
Factor w/ 2 levels "male","female"	[,4]
smok	Factor w/ 2 levels "smoker","non"
[,5]	emp
Factor w/ 3 levels "<10","10-20",...< td="">	[,6]
yes	int, Number of workers who suffered byssinosis