R Dataset / Package COUNT / azcabgptca

How To Create a Barplot

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Visual
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How To Create a Stacked Barplot

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How To Create a Pie Chart

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How To Compute the Mean

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Numerical
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How To Create a Plot

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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

Submitted by pmagunia on April 22, 2018 - 3:08 PM
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Cumulative Frequency Histogram

Submitted by pmagunia on April 22, 2018 - 3:09 PM
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Dotplot

Submitted by pmagunia on April 22, 2018 - 3:10 PM
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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

Submitted by pmagunia on April 22, 2018 - 3:12 PM

Stem and Leaf Plots

Submitted by pmagunia on April 22, 2018 - 3:12 PM
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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
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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
Documentation

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.


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.
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      2. Relative Frequency Histogram
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