R Dataset / Package COUNT / fasttrakg

On this R-data statistics page, you will find information about the fasttrakg data set which pertains to fasttrakg. The fasttrakg data set is found in the COUNT R package. You can load the fasttrakg data set in R by issuing the following command at the console data("fasttrakg"). This will load the data into a variable called fasttrakg. If R says the fasttrakg 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 with the library() command. 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 fasttrakg R data set. The size of this file is about 361 bytes.

fasttrakg

Description

Data are from the Canadian National Cardiovascular Disease registry called, FASTRAK. years covered at 1996-1998. They have been grouped by covariate patterns from individual observations.

Usage

data(fasttrakg)

Format

A data frame with 15 observations on the following 9 variables.

die: number died from MI
cases: number of cases with same covariate pattern
anterior: 1=anterior site MI; 0=inferior site MI
hcabg: 1=history of CABG; 0=no history of CABG
killip: Killip level of cardiac event severity (1-4)age75

1= Age>75; 0=Age<=75

kk1: (1/0) angina; not MI
kk2: (1/0) moderate severity cardiac event
kk3: (1/0) Severe cardiac event
kk4: (1/0) Severe cardiac event; death

Details

fasttrakg is saved as a data frame. Count models use died as response numerator and cases as the demoninator

Source

1996-1998 FASTRAK data, Hoffman-LaRoche Canada, National Health Economics & Research Co.

References

Hilbe, Joseph M (2007, 2011), Negative Binomial Regression, Cambridge University Press Hilbe, Joseph M (2009), Logistic Regression Models, Chapman & Hall/CRC Hilbe, Joseph M (2014), Modeling Count Data, Cambridge University Press

Examples

library(MASS)
data(fasttrakg)
glmfp <- glm(die ~ anterior + factor(killip) + offset(log(cases)), family=poisson, data=fasttrakg)
summary(glmfp)
exp(coef(glmfp))

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

Attachments: csv, json

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