DoctorRWM {DiSSMod}

German doctor first visits data

Description

Data is from Riphahn, Wambach and Million (2003), used for studying longitudinal analysis concerning the usage of the German health insurance system. The original data contain a few years data for patients, but we have only for first year.

Usage

data(DoctorRWM)

Format

A data frame with 7293 observations of 26 variables as below;

ID

identification number (numeric)

FEMALE

female or not (categorical)

YEAR

year (categorical)

AGE

age (numeric)

HSAT

health satisfaction coded 0 (low) to 10 (high) (numeric)

HANDDUM

person is handicappe or not (categorical)

HANDPER

percentage degree of handicap (numeric)

HHNINC

monthly household net income (numeric)

HHKIDS

child (ren) below age 16 in household (numeric)

EDUC

years of schooling (numeric)

MARRIED

person is married or not (categorical)

HAUPTS

level of schooling (categorical)

REALS

level of schooling (categorical)

FACHHS

level of schooling (categorical)

ABITUR

level of schooling (categorical)

UNIV

level of schooling (categorical)

WORKING

employed or not (categorical)

BLUEC

person is blue collar worker or not (categorical)

WHITEC

person is white collar worker or not (categorical)

SELF

person is self-employed or not (categorical)

BEAMT

civil servant or not (categorical)

DOCVIS

number of doctor visits in last 3 months (numeric)

HOSPVIS

number of hospital visits last year (numeric)

PUBLIC

person is insured in public health insurance or not (categorical)

ADDON

person is insured in add-on insurance or not (categorical)

INCOME_SCALE

scaled income; original income/1000 (numeric)

Source

Riphahn, R. T., Wambach, A. and Million, A. (2003) Incentive Effects in the Demand for Health Care: A Bivariate Panel Count Data Estimation, Journal of Applied Econometrics, 18, 4, 387–405. Published online 8 October 2002. https://doi.org/10.1002/jae.680

http://qed.econ.queensu.ca/jae/2003-v18.4/riphahn-wambach-million/

References

Greene, W. H. (2012) Econometric Analysis, 7th Edition. Pearson education.

Azzalini, A., Kim, H.-M. and Kim, H.-J. (2019) Sample selection models for discrete and other non-Gaussian response variables. Statistical Methods & Applications, 28, 27–56. First online 30 March 2018. https://doi.org/10.1007/s10260-018-0427-1