+----------+-------------------+
| rwm5yr   | R Documentation   |
+----------+-------------------+

rwm5yr
------

Description
~~~~~~~~~~~

German health registry for the years 1984-1988. Health information for
years immediately prior to health reform.

Usage
~~~~~

::

    data(rwm5yr)

Format
~~~~~~

A data frame with 19,609 observations on the following 17 variables.

``id``
    patient ID (1=7028)

``docvis``
    number of visits to doctor during year (0-121)

``hospvis``
    number of days in hospital during year (0-51)

``year``
    year; (categorical: 1984, 1985, 1986, 1987, 1988)

``edlevel``
    educational level (categorical: 1-4)

``age``
    age: 25-64

``outwork``
    out of work=1; 0=working

``female``
    female=1; 0=male

``married``
    married=1; 0=not married

``kids``
    have children=1; no children=0

``hhninc``
    household yearly income in marks (in Marks)

``educ``
    years of formal education (7-18)

``self``
    self-employed=1; not self employed=0

``edlevel1``
    (1/0) not high school graduate

``edlevel2``
    (1/0) high school graduate

``edlevel3``
    (1/0) university/college

``edlevel4``
    (1/0) graduate school

Details
~~~~~~~

rwm5yr is saved as a data frame. Count models typically use docvis as
response variable. 0 counts are included

Source
~~~~~~

German Health Reform Registry, years pre-reform 1984-1988,

References
~~~~~~~~~~

Hilbe, Joseph M (2007, 2011), Negative Binomial Regression, Cambridge
University Press

Examples
~~~~~~~~

::

    data(rwm5yr)
    glmrp <- glm(docvis ~ outwork + female + age + factor(edlevel), family=poisson, data=rwm5yr)
    summary(glmrp)
    exp(coef(glmrp))
    library(MASS)
    glmrnb <- glm.nb(docvis ~ outwork + female + age + factor(edlevel), data=rwm5yr)
    summary(glmrnb)
    exp(coef(glmrnb))
    ## Not run: 
    library(gee)
    mygee <- gee(docvis ~ outwork + age + factor(edlevel), id=id, 
      corstr = "exchangeable", family=poisson, data=rwm5yr)
    summary(mygee)
    exp(coef(mygee))

    ## End(Not run)

