azdrg112

Description

The data set relates to the hospital length of stay for patients having a CABG or PTCA (typel) heart procedure. The data comes from the 1995 Arizona Medicare data for DRG (Diagnostic Related Group) 112. Other predictors include gender(1=female) and age75 (1-age 75+). Type is labeled as 1=emergency or urgent admission; 0= elective. Length of stay (los) ranges from 1 to 53 days.

Usage

data(azdrg112)

Format

A data frame with 1,798 observations on the following 4 variables.

los

hospital length of stay: 1-53 days

gender

1=male; 0=female

type1

1=emergency/urgent admission; 0=elective admission

age75

1=age>75; 0=age<=75

Details

azdrg112 is saved as a data frame. Count models typically use los as response variable. 0 counts are not included

Source

DRG 112 data from the 1995 Arizona Medicare (MedPar) State files

References

Hilbe, Joseph M (2007, 2011), Negative Binomial Regression, Cambridge University Press

Examples

data(azdrg112)
glmazp <- glm(los ~ type1 + gender + age75, family=poisson, data=azdrg112)
summary(glmazp)
exp(coef(glmazp))
library(MASS)
glmaznb <- glm.nb(los ~ type1 + gender + age75, data=azdrg112)
summary(glmaznb)
exp(coef(glmaznb))

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> 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/azdrg112.Rd_%03d_medium.png", width=480, height=480)
> ### Name: azdrg112
> ### Title: azdrg112
> ### Aliases: azdrg112
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data(azdrg112)
> glmazp <- glm(los ~ type1 + gender + age75, family=poisson, data=azdrg112)
> summary(glmazp)

Call:
glm(formula = los ~ type1 + gender + age75, family = poisson, 
    data = azdrg112)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-2.8352  -1.0785  -0.4225   0.6337  11.6269  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  1.18224    0.02759  42.844  < 2e-16 ***
type1        0.62804    0.02584  24.309  < 2e-16 ***
gender      -0.14745    0.02184  -6.752 1.45e-11 ***
age75        0.12978    0.02317   5.602 2.12e-08 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for poisson family taken to be 1)

    Null deviance: 4145.2  on 1797  degrees of freedom
Residual deviance: 3364.0  on 1794  degrees of freedom
AIC: 9178.5

Number of Fisher Scoring iterations: 5

> exp(coef(glmazp))
(Intercept)       type1      gender       age75 
  3.2616583   1.8739345   0.8629032   1.1385801 
> library(MASS)
> glmaznb <- glm.nb(los ~ type1 + gender + age75, data=azdrg112)
> summary(glmaznb)

Call:
glm.nb(formula = los ~ type1 + gender + age75, data = azdrg112, 
    init.theta = 5.449919402, link = log)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-2.1261  -0.8054  -0.2910   0.4843   6.2802  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  1.18600    0.03602  32.925  < 2e-16 ***
type1        0.62635    0.03344  18.730  < 2e-16 ***
gender      -0.14690    0.03064  -4.795 1.63e-06 ***
age75        0.11990    0.03275   3.661 0.000251 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for Negative Binomial(5.4499) family taken to be 1)

    Null deviance: 2098.5  on 1797  degrees of freedom
Residual deviance: 1675.0  on 1794  degrees of freedom
AIC: 8568.9

Number of Fisher Scoring iterations: 1


              Theta:  5.450 
          Std. Err.:  0.366 

 2 x log-likelihood:  -8558.917 
> exp(coef(glmaznb))
(Intercept)       type1      gender       age75 
   3.273966    1.870767    0.863378    1.127388 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>