R Dataset / Package car / Wong

Documentation

On this Picostat.com statistics page, you will find information about the Wong data set which pertains to Post-Coma Recovery of IQ. The Wong data set is found in the car R package. You can load the Wong data set in R by issuing the following command at the console data("Wong"). This will load the data into a variable called Wong. If R says the Wong data set is not found, you can try installing the package by issuing this command install.packages("car") 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 Wong R data set. The size of this file is about 11,313 bytes.


Post-Coma Recovery of IQ

Description

The Wong data frame has 331 row and 7 columns. The observations are longitudinal data on recovery of IQ after comas of varying duration for 200 subjects.

Usage

Wong

Format

This data frame contains the following columns:

id

patient ID number.

days

number of days post coma at which IQs were measured.

duration

duration of the coma in days.

sex

a factor with levels Female and Male.

age

in years at the time of injury.

piq

performance (i.e., mathematical) IQ.

viq

verbal IQ.

Details

The data are from Wong, Monette, and Weiner (2001) and are for 200 patients who sustained traumatic brain injuries resulting in comas of varying duration. After awakening from their comas, patients were periodically administered a standard IQ test, but the average number of measurements per patient is small (331/200 = 1.7).

Source

Wong, P. P., Monette, G., and Weiner, N. I. (2001) Mathematical models of cognitive recovery. Brain Injury, 15, 519–530.

References

Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.

Examples

summary(Wong)
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Dataset imported from https://www.r-project.org.

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Attachment Size
dataset-85577.csv 11.05 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0