R Dataset / Package Ecdat / OFP

On this R-data statistics page, you will find information about the OFP data set which pertains to Visits to Physician Office . The OFP data set is found in the Ecdat R package. You can load the OFP data set in R by issuing the following command at the console data("OFP"). This will load the data into a variable called OFP. If R says the OFP data set is not found, you can try installing the package by issuing this command install.packages("Ecdat") and then attempt to reload the data with the library() command. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the OFP R data set. The size of this file is about 357,798 bytes.

Visits to Physician Office

Description

a cross-section

number of observations : 4406

observation : individuals

country : United States

Usage

data(OFP)

Format

A dataframe containing :

ofp: number of physician office visits
ofnp: number of nonphysician office visits
opp: number of physician outpatient visits
opnp: number of nonphysician outpatient visits
emr: number of emergency room visits
hosp: number of hospitalizations
numchron: number of chronic conditions
adldiff: the person has a condition that limits activities of daily living ?
age: age in years (divided by 10)
black: is the person african–american ?
sex: is the person male ?
maried: is the person maried ?
school: number of years of education
faminc: family income in 10000\$
employed: is the person employed ?
privins: is the person covered by private health insurance ?
medicaid: is the person covered by medicaid ?
region: the region (noreast, midwest,west)
hlth: self-perceived health (excellent, poor, other)

Source

Deb, P. and P.K. Trivedi (1997) “Demand for Medical Care by the Elderly: A Finite Mixture Approach”, Journal of Applied Econometrics, 12, 313-326..

References

Cameron, A.C. and Trivedi P.K. (1998) Regression analysis of count data, Cambridge University Press, http://cameron.econ.ucdavis.edu/racd/racddata.html, chapter 6.

Journal of Applied Econometrics data archive : http://qed.econ.queensu.ca/jae/.

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