R Dataset / Package COUNT / badhealth

How To Create a Barplot

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Visual
Instructional

How To Create a Stacked Barplot

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Visual
Instructional

How To Create a Pie Chart

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Visual

How To Compute the Mean

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Numerical
Instructional

How To Create a Plot

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Visual
Instructional

How to Compute the Median

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Numerical

Boxplot

Submitted by pmagunia on April 22, 2018 - 3:07 PM
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Correlation Coefficient

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Cumulative Frequency Histogram

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Dotplot

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Hollow Histogram

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Numerical Summaries

Submitted by pmagunia on April 22, 2018 - 2:51 PM
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Pie Chart

Submitted by pmagunia on April 22, 2018 - 3:11 PM
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Plot

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Regression

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Stem and Leaf Plots

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Visual Summaries

Submitted by pmagunia on April 22, 2018 - 3:13 PM
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Submitted by pmagunia on March 9, 2018 - 1:06 PM
<iframe src="https://embed.picostat.com/r-dataset-package-count-badhealth.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-90943.csv 7.78 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Documentation

On this Picostat.com statistics page, you will find information about the badhealth data set which pertains to badhealth. The badhealth data set is found in the COUNT R package. You can load the badhealth data set in R by issuing the following command at the console data("badhealth"). This will load the data into a variable called badhealth. If R says the badhealth data set is not found, you can try installing the package by issuing this command install.packages("COUNT") and then attempt to reload the data. 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 badhealth R data set. The size of this file is about 7,967 bytes.


badhealth

Description

From German health survey data for the year 1998 only.

Usage

data(badhealth)

Format

A data frame with 1,127 observations on the following 3 variables.

numvisit

number of visits to doctor during 1998

badh

1=patient claims to be in bad health; 0=not in bad health

age

age of patient: 20-60

Details

badhealth is saved as a data frame. Count models use numvisit as the response variable, 0 counts are included.

Source

German Health Survey, amended in Hilbe and Greene (2008).

References

Hilbe, Joseph M (2011), Negative Binomial Regression, Cambridge University Press Hilbe, J. and W. Greene (2008). Count Response Regression Models, in ed. C.R. Rao, J.P Miller, and D.C. Rao, Epidemiology and Medical Statistics, Elsevier Handbook of Statistics Series. London, UK: Elsevier.

Examples

data(badhealth)
glmbadp <- glm(numvisit ~ badh + age, family=poisson, data=badhealth)
summary(glmbadp)
exp(coef(glmbadp))
library(MASS)
glmbadnb <- glm.nb(numvisit ~ badh + age, data=badhealth)
summary(glmbadnb)
exp(coef(glmbadnb))

--

Dataset imported from https://www.r-project.org.
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R Output Date
Picostat Output - Simple Linear Regression Nov 27, 2018
Picostat Output - Simple Linear Regression Nov 27, 2018
Picostat Output - Simple Linear Regression Nov 27, 2018
Picostat Output - Simple Linear Regression Nov 27, 2018
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