Earnings: Gelman and Hill's Earnings and Height Data.

In R4HCR: R for Health Care Research

Gelman and Hill's Earnings and Height Data.

Description

Data from a survey of adult Americans in 1994.

Usage

Earnings

Format

A data frame with 1192 observations on the following 4 variables.

earn

Annual earnings (in dollars).

sex

Sex (1 = men, 2 = women).

yearbn

Year of birth.

height

Height (in inches).

Details

This is a subset of the data was used in a number of regression examples in Data analysis using regression and multilevel/hierarchical models by Gelman and Hill (2006).

Source

http://www.stat.columbia.edu/~gelman/arm/software/

References

Gelman, Andrew, and Jennifer Hill. Data Analysis Using Regression and Multilevel/Hierarchical models. Cambridge university press, 2006.

Persico, Nicola, Andrew Postlewaite, and Dan Silverman. "The effect of adolescent experience on labor market outcomes: the case of height (No. w10522)." (2004).

Examples

data(Earnings, package = "R4HCR")

mod <- lm(earn ~ height, data = Earnings)

# % variation explained
summary(mod)$adj.r.squared

# regression coefficients.
coef(mod)

# log earnings model
logm <- lm(I(log(earn)) ~ height, data = Earnings)
coef(logm)

R4HCR documentation built on Sept. 30, 2024, 9:46 a.m.