R Dataset / Package COUNT / azcabgptca

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Attachment	Size
dataset-86370.csv	25.48 KB

Dataset License

GNU General Public License v2.0

Documentation License

GNU General Public License v2.0

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Dataset Help
On this Picostat.com statistics page, you will find information about the azcabgptca data set which pertains to azcabgptca. The azcabgptca data set is found in the COUNT R package. You can load the azcabgptca data set in R by issuing the following command at the console data("azcabgptca"). This will load the data into a variable called azcabgptca. If R says the azcabgptca 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 azcabgptca R data set. The size of this file is about 26,093 bytes.

Dataset Help

On this Picostat.com statistics page, you will find information about the azcabgptca data set which pertains to azcabgptca. The azcabgptca data set is found in the COUNT R package. You can load the azcabgptca data set in R by issuing the following command at the console data("azcabgptca"). This will load the data into a variable called azcabgptca. If R says the azcabgptca 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 azcabgptca R data set. The size of this file is about 26,093 bytes.

Documentation

Documentation
azcabgptca Description Random subset of the 1991 Arizona Medicare data for patients hospitalized subsequent to undergoing a CABG (DRGs 106, 107) or PTCA (DRG 112) cardiovascular procedure. Usage data(azcabgptca) Format A data frame with 1959 observations on the following 6 variables. `died` systolic blood pressure of subject `procedure` 1=CABG; 0=PTCA `gender` 1=male; 0=female `age` age of subject `los` hospital length of stay `type` 1=emerg/urgent; 0=elective Details azcabgptca is saved as a data frame. Source Hilbe, Negative Binomial Regression, 2nd ed, Cambridge Univ Press References Hilbe, Joseph M (2014), Modeling Count Data, Cambridge University Press Examples data(azcabgptca); attach(azcabgptca) table(los); table(procedure, type); table(los, procedure) summary(los) summary(c91a <- glm(los ~ procedure+ type, family=poisson, data=azcabgptca)) modelfit(c91a) summary(c91b <- glm(los ~ procedure+ type, family=quasipoisson, data=azcabgptca)) modelfit(c91b) library(sandwich) sqrt(diag(vcovHC(c91a, type="HC0"))) -- Dataset imported from https://www.r-project.org.

azcabgptca

Description

Random subset of the 1991 Arizona Medicare data for patients hospitalized subsequent to undergoing a CABG (DRGs 106, 107) or PTCA (DRG 112) cardiovascular procedure.

Usage

data(azcabgptca)

Format

A data frame with 1959 observations on the following 6 variables.

died: systolic blood pressure of subject
procedure: 1=CABG; 0=PTCA
gender: 1=male; 0=female
age: age of subject
los: hospital length of stay
type: 1=emerg/urgent; 0=elective

Details

azcabgptca is saved as a data frame.

Source

Hilbe, Negative Binomial Regression, 2nd ed, Cambridge Univ Press

References

Hilbe, Joseph M (2014), Modeling Count Data, Cambridge University Press

Examples

data(azcabgptca); attach(azcabgptca)
table(los); table(procedure, type); table(los, procedure)
summary(los)
summary(c91a <- glm(los ~ procedure+ type, family=poisson, data=azcabgptca))
modelfit(c91a)
summary(c91b <- glm(los ~ procedure+ type, family=quasipoisson, data=azcabgptca))
modelfit(c91b)
library(sandwich)
sqrt(diag(vcovHC(c91a, type="HC0")))

--

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

Curated Data	File Size
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PSID
wage1	328 bytes
OpenIntro Statistics Dataset - yrbss_samp	7.62 KB
OpenIntro Statistics Dataset - yrbss	1.03 MB
OpenIntro Statistics Dataset - yawn	861 bytes

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PICOSTAT

R Dataset / Package COUNT / azcabgptca

How To Create a Barplot

How To Create a Stacked Barplot

How To Create a Pie Chart

How To Compute the Mean

How To Create a Plot

How to Compute the Median

Boxplot

Correlation Coefficient

Cumulative Frequency Histogram

Dotplot

Hollow Histogram

Numerical Summaries

Pie Chart

Plot

Regression

Stem and Leaf Plots

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azcabgptca

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