I am having trouble recreating an analysis using the standard
hosmer-lemeshow dataset cited in V&R 3rd edition.
P.222 Venables and Ripley
Relevant section of the analysis:
> options(constrasts=c("contr.treatment","contr.poly"))
> race<-factor(RACE,labels=c("white","black","other"))
> table(race,as.numeric(race))
1 2 3
white 96 0 0
black 0 26 0
other 0 0 67
> ftv<-factor(FTV)
> levels(ftv)[-(1:2)]<-"2+"
> table(ftv)
0 1 2+
100 47 42
>
bbwt<-data.frame(low=factor(LOW),AGE,LWT,race,smoke=(SMOKE>0),ptd,ht=HT>0,ui=(UI>0),ftv)
> birthwt.glm<-glm(low~.,family=binomial,data=bbwt)
> summary(birthwt.glm,corr=F)
Call: glm(formula = low ~ AGE + LWT + race + smoke + ptd + ht + ui +
ftv, family = binomial, data =
bbwt
)
Deviance Residuals:
Min 1Q Median 3Q Max
-1.703806 -0.8067671 -0.5008365 0.8835519 2.215185
Coefficients:
Value Std. Error t value
(Intercept) 3.72790660 1.344892247 2.7718998
AGE -0.03723398 0.038677748 -0.9626718
LWT -0.01565297 0.007075944 -2.2121383
race1 0.59620460 0.267872879 2.2256998
race2 0.04815882 0.144406014 0.3334960
smoke 0.37776250 0.212382233 1.7786916
ptd 0.67188041 0.240222259 2.7969115
ht 0.95658085 0.360217203 2.6555668
ui 0.34009734 0.232107790 1.4652560
ftv1 -0.21818928 0.239580527 -0.9107138
ftv2 0.13239878 0.148931932 0.8889885
(Dispersion Parameter for Binomial family taken to be 1 )
Null Deviance: 234.672 on 188 degrees of freedom
Residual Deviance: 195.4755 on 178 degrees of freedom
Number of Fisher Scoring Iterations: 4
Note: race2 and ftv2 Are not the same as the results in the Venables
and Ripley book. The value of the coefficients given by Venables and
Ripley P. 223 third edition are .7406 and .179007 respectively.
I am assuming that race1 is comparing race=2 to race=1 and that race2 is
comparing race=3 to race=1.
For those who do not have the dataset, I would be happy to forward.
Is there some change in the coding of splus 2000?
Sincerely,
Eran Bellin
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