R Dataset / Package vcd / Arthritis

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

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Cumulative Frequency Histogram

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Dotplot

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Hollow Histogram

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Numerical Summaries

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Pie Chart

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Plot

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Ratio

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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-54845.csv 2.66 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 Arthritis data set which pertains to Arthritis Treatment Data. The Arthritis data set is found in the vcd R package. Try to load the Arthritis data set in R by issuing the following command at the console data("Arthritis"). This may load the data into a variable called Arthritis. If R says the Arthritis data set is not found, you can try installing the package by issuing this command install.packages("vcd") and then attempt to reload the data with library("vcd") followed by data("Arthritis"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing Arthritis at the command-line which should display the entire dataset.

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 Arthritis R data set. The size of this file is about 2,725 bytes.


Arthritis Treatment Data

Description

Data from Koch \& Edwards (1988) from a double-blind clinical trial investigating a new treatment for rheumatoid arthritis.

Usage

data("Arthritis")

Format

A data frame with 84 observations and 5 variables.

ID

patient ID.

Treatment

factor indicating treatment (Placebo, Treated).

Sex

factor indicating sex (Female, Male).

Age

age of patient.

Improved

ordered factor indicating treatment outcome (None, Some, Marked).

Source

Michael Friendly (2000), Visualizing Categorical Data: http://euclid.psych.yorku.ca/ftp/sas/vcd/catdata/arthrit.sas

References

G. Koch \& S. Edwards (1988), Clinical efficiency trials with categorical data. In K. E. Peace (ed.), Biopharmaceutical Statistics for Drug Development, 403–451. Marcel Dekker, New York.

M. Friendly (2000), Visualizing Categorical Data. SAS Institute, Cary, NC.

Examples

data("Arthritis")
art <- xtabs(~ Treatment + Improved, data = Arthritis, subset = Sex == "Female")
artmosaic(art, gp = shading_Friendly)
mosaic(art, gp = shading_max)

--

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