DoctorVisits: Australian Health Service Utilization Data

Description

Cross-section data originating from the 1977--1978 Australian Health Survey.

Usage

data("DoctorVisits")

Arguments

Format

A data frame containing 5,190 observations on 12 variables.

visits: Number of doctor visits in past 2 weeks.
gender: Factor indicating gender.
age: Age in years divided by 100.
income: Annual income in tens of thousands of dollars.
illness: Number of illnesses in past 2 weeks.
reduced: Number of days of reduced activity in past 2 weeks due to illness or injury.
health: General health questionnaire score using Goldberg's method.
private: Factor. Does the individual have private health insurance?
freepoor: Factor. Does the individual have free government health insurance due to low income?
freerepat: Factor. Does the individual have free government health insurance due to old age, disability or veteran status?
nchronic: Factor. Is there a chronic condition not limiting activity?
lchronic: Factor. Is there a chronic condition limiting activity?

References

Cameron, A.C. and Trivedi, P.K. (1986). Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests. Journal of Applied Econometrics, 1, 29--53.

Cameron, A.C. and Trivedi, P.K. (1998). Regression Analysis of Count Data. Cambridge: Cambridge University Press.

Mullahy, J. (1997). Heterogeneity, Excess Zeros, and the Structure of Count Data Models. Journal of Applied Econometrics, 12, 337--350.

Examples

Run this code

# NOT RUN {
data("DoctorVisits", package = "AER")
library("MASS")

## Cameron and Trivedi (1986), Table III, col. (1)
dv_lm <- lm(visits ~ . + I(age^2), data = DoctorVisits)
summary(dv_lm)

## Cameron and Trivedi (1998), Table 3.3 
dv_pois <- glm(visits ~ . + I(age^2), data = DoctorVisits, family = poisson)
summary(dv_pois)                  ## MLH standard errors
coeftest(dv_pois, vcov = vcovOPG) ## MLOP standard errors
logLik(dv_pois)
## standard errors denoted RS ("unspecified omega robust sandwich estimate")
coeftest(dv_pois, vcov = sandwich)

## Cameron and Trivedi (1986), Table III, col. (4)
dv_nb <- glm.nb(visits ~ . + I(age^2), data = DoctorVisits)
summary(dv_nb)
logLik(dv_nb)
# }