eyes {SMPracticals}

Visual Impairment Data

Description

Joint distribution of visual impairment on both eyes, by race and age.

Usage

data(eyes)

Format

A data frame with 32 observations on the following 6 variables.

L

Impairment (+) or not (-) for left eye.

R

Impairment (+) or not (-) for right eye.

age

a factor with levels 40-50 51-60 61-70 70+

colour

White (W) or black (B)

a

mid-point for age groups, as numeric vector

y

Number of individuals in each class

Source

K.-Y. Liang, S. L. Zeger and B. Qaqish (1992) Multivariate regression analyses for categorical data (with Discussion). Journal of the Royal Statistical Society, series B, 54, 3–40.

References

Davison, A. C. (2003) Statistical Models. Cambridge University Press. Page 505.

Examples

data(eyes)
eyes.glm <- glm(y~age*colour+L*R+(L+R):poly(a,2)+colour:(L+R),poisson,data=eyes)
anova(eyes.glm,test="Chi")   # analysis of deviance for loglinear model