Description Usage Arguments Format Details Value Note Author(s) References See Also Examples
Following the glm() function with a grouped binomial or poisson family, or glm.nb(), P__disp() displays the Pearson Chi2 statistic and related dispersion statistic. Values of the dispersion greater than 1.0 indicate possible overdispersion; values under 1.0 indicate possible underdispersion.
1 | P__disp(x)
|
x |
glm object |
The only argument is the name of the fitted glm or glm.nb function model
P_disp is a post-estimation function, following the use of glm() or glm.nb(). Appropriate with grouped binomial or Poisson glm families.
Pearson Chi2 statistic
Pearson dispersion: Chi2/dof
P__disp must be loaded into memory in order to be effectve. As a function in LOGIT, it is immediately available to a user.
Joseph M. Hilbe, Arizona State University, and Jet Propulsion Laboratory, California Institute of technology
Hilbe, Joseph M. (2015), Practical Guide to Logistic Regression, Chapman & Hall/CRC. Hilbe, Joseph M. (2014), Modeling Count Data, Cambridge University Press
1 2 3 4 5 6 7 8 9 | library(MASS)
library(LOGIT)
data(titanicgrp)
class03 <- factor(titanicgrp$class, levels=c("3rd class", "2nd class", "1st class"))
died <- titanicgrp$cases - titanicgrp$survive
grptit <- glm( cbind(survive, died) ~ age+sex+class03, family=binomial,
data=titanicgrp)
summary(grptit)
P__disp(grptit)
|
Call:
glm(formula = cbind(survive, died) ~ age + sex + class03, family = binomial,
data = titanicgrp)
Deviance Residuals:
Min 1Q Median 3Q Max
-4.232 -2.365 1.038 3.180 4.362
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 1.2955 0.2478 5.227 1.72e-07 ***
ageadults -1.0556 0.2427 -4.350 1.36e-05 ***
sexman -2.3695 0.1453 -16.313 < 2e-16 ***
class032nd class 0.7558 0.1753 4.313 1.61e-05 ***
class031st class 1.7664 0.1707 10.347 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 581.40 on 11 degrees of freedom
Residual deviance: 110.84 on 7 degrees of freedom
AIC: 157.77
Number of Fisher Scoring iterations: 5
Pearson Chi2 = 100.8828
Dispersion = 14.41183
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