R Dataset / Package COUNT / mdvis

Submitted by pmagunia on March 9, 2018 - 1:06 PM
Dataset License
GNU General Public License v2.0
Attachment Size
dataset-72455.csv 91.35 KB
Documentation

mdvis

Description

Data from a subset of the German Socio-Economic Panel (SOEP). The subset was created by Rabe-Hesketh and Skrondal (2005). Only working women are included in these data. Beginning in 1997, German health reform in part entailed a 200 co-payment as well as limits in provider reimbursement. Patients were surveyed for the one year panel (1996) prior to and the one year panel (1998) after reform to assess whether the number of physician visits by patients declined - which was the goal of reform legislation. The response, or variable to be explained by the model, is numvisit, which indicates the number of patient visits to a physician's office during a three month period.

Usage

data(mdvis)

Format

A data frame with 2,227 observations on the following 13 variables.

numvisit

visits to MD office 3mo prior

reform

1=interview yr post-reform: 1998;0=pre-reform:1996

badh

1=bad health; 0 = not bad health

age

Age(yrs 20-60)

educ

education(1:7-10;2=10.5-12;3=HSgrad+)

educ1

educ1= 7-10 years

educ2

educ2= 10.5-12 years

educ3

educ3= post secondary or high school

agegrp

age: 1=20-39; 2=40-49; 3=50-60

age1

age 20-39

age2

age 40-49

age3

age 50-60

loginc

log(household income in DM)

Details

mdvis is saved as a data frame. Count models typically use docvis as response variable. 0 counts are included

Source

German Socio-Economic Panel (SOEP), 1995 pre-reform; 1998 post reform. Created by Rabe-Hesketh and Skrondal (2005).

References

Hilbe, Joseph M (2007, 2011), Negative Binomial Regression, Cambridge University Press Hilbe, Joseph M (2009), Logistic Regression Models, Chapman & Hall/CRC Rabe-Hesketh, S. and A. Skrondal (2005). Multilevel and Longitudinal Modeling Using Stata, College Station: Stata Press.

Examples

data(mdvis)
glmmdp <- glm(numvisit ~ reform + factor(educ) + factor(agegrp), family=poisson, data=mdvis)
summary(glmmdp)
exp(coef(glmmdp))
library(MASS)
glmmdnb <- glm.nb(numvisit ~ reform + factor(educ) + factor(agegrp), data=mdvis)
summary(glmmdnb)
exp(coef(glmmdnb))
--

Dataset imported from https://www.r-project.org.

Documentation License
GNU General Public License v2.0

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