toRR: Display count model coefficient table as incidence rate...

In LOGIT: Functions, Data and Code for Binary and Binomial Data

Description

Following the glm or glm.nb commands, toRR() displays a table of incidence rate ratios and related statistics including exponentiated model confidence intervals.

Usage

toRR(object)

Arguments

object

name of the fitted glm function model

Format

object

The only argument is the name of the fitted glm or glm.nb function model

or

incidence rate ratio of predictor

delta

Model standard error using delta method

zscore

z-statistic

pvalue

probability-value based on normal distribution

exp.loci

Exponentialed lower model confidence interval

exp.upci

Expontiated upper model confidence interval

Details

toRR is a post-estimation function, following the use of glm() with the Poisson or negative.binomial families, and following glm.nb().

Value

list

Note

toRR must be loaded into memory in order to be effectve. As a function in LOGIT, it is immediately available to a user.

Author(s)

Joseph M. Hilbe, Arizona State University, and Jet Propulsion Laboratory, California Institute of technology

References

Hilbe, Joseph M. (2015), Practical Guide to Logistic Regression, Chapman & Hall/CRC.

Hilbe, Joseph M. (2014), Modeling Count Data, Cambridge University Press.

See Also

glm, glm.nb

Examples

library(MASS)
library(LOGIT)
data(medpar)
medpar$los<-as.numeric(medpar$los)
mypoi <- glm(los ~ white + hmo + factor(age80), family=poisson, data=medpar)
summary(mypoi)
toRR(mypoi)

Example output

Call:
glm(formula = los ~ white + hmo + factor(age80), family = poisson, 
    data = medpar)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-4.1497  -1.7828  -0.6709   0.8897  18.8565  

Coefficients:
               Estimate Std. Error z value Pr(>|z|)    
(Intercept)     2.49348    0.02607  95.636  < 2e-16 ***
white          -0.18587    0.02731  -6.805 1.01e-11 ***
hmo            -0.14485    0.02375  -6.100 1.06e-09 ***
factor(age80)1 -0.07124    0.02032  -3.506 0.000456 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for poisson family taken to be 1)

    Null deviance: 8901.1  on 1494  degrees of freedom
Residual deviance: 8800.5  on 1491  degrees of freedom
AIC: 14524

Number of Fisher Scoring iterations: 5

                    rr  delta  zscore pvalue exp.loci. exp.upci.
(Intercept)    12.1033 0.3156 95.6360  0e+00   11.5003   12.7379
white           0.8304 0.0227 -6.8049  0e+00    0.7871    0.8760
hmo             0.8651 0.0205 -6.0996  0e+00    0.8258    0.9064
factor(age80)1  0.9312 0.0189 -3.5056  5e-04    0.8949    0.9691

LOGIT documentation built on May 29, 2017, 10:26 a.m.