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))

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(COUNT)
Loading required package: msme
Loading required package: MASS
Loading required package: lattice
Loading required package: sandwich
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/COUNT/fasttrakg.Rd_%03d_medium.png", width=480, height=480)
> ### Name: fasttrakg
> ### Title: fasttrakg
> ### Aliases: fasttrakg
> ### Keywords: datasets
> 
> ### ** Examples
> 
> library(MASS)
> data(fasttrakg)
> glmfp <- glm(die ~ anterior + factor(killip) + offset(log(cases)), family=poisson, data=fasttrakg)
> summary(glmfp)

Call:
glm(formula = die ~ anterior + factor(killip) + offset(log(cases)), 
    family = poisson, data = fasttrakg)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-1.5980  -0.5396   0.4240   0.8004   2.2171  

Coefficients:
                Estimate Std. Error z value Pr(>|z|)    
(Intercept)      -4.0378     0.1444 -27.961  < 2e-16 ***
anterior          0.6618     0.1593   4.154 3.26e-05 ***
factor(killip)2   0.9131     0.1722   5.303 1.14e-07 ***
factor(killip)3   1.1280     0.2511   4.493 7.02e-06 ***
factor(killip)4   2.5027     0.2743   9.124  < 2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for poisson family taken to be 1)

    Null deviance: 116.232  on 14  degrees of freedom
Residual deviance:  14.331  on 10  degrees of freedom
AIC: 75.391

Number of Fisher Scoring iterations: 5

> exp(coef(glmfp))
    (Intercept)        anterior factor(killip)2 factor(killip)3 factor(killip)4 
     0.01763579      1.93835615      2.49204666      3.08955682     12.21486088 
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>