[R] Help with "non-integer #successes in a binomial glm"

From: Haibo Huang <edhuang00_at_yahoo.com>
Date: Tue 09 Aug 2005 - 07:06:48 EST


Hi,

I had a logit regression, but don't really know how to handle the "Warning message: non-integer #successes in a binomial glm! in: eval(expr, envir, enclos)" problem. I had the same logit regression without weights and it worked out without the warning, but I figured it makes more sense to add the weights. The weights sum up to one.

Could anyone give me some hint? Thanks a lot!

FYI, I have posted both regressions (with and without weights) below.

Ed

> setwd("P:/Work in Progress/Haibo/Hans")
>
> Lease=read.csv("lease.csv", header=TRUE)
> Lease$ET <- factor(Lease$EarlyTermination)
> SICCode=factor(Lease$SIC.Code)
> Lease$TO=factor(Lease$TenantHasOption)
> Lease$LO=factor(Lease$LandlordHasOption)
> Lease$TEO=factor(Lease$TenantExercisedOption)
>
> RegA=glm(ET~1+TO,
+ family=binomial(link=logit), data=Lease)
> summary(RegA)

Call:
glm(formula = ET ~ 1 + TO, family = binomial(link = logit), data = Lease)

Deviance Residuals:

    Min 1Q Median 3Q Max -0.5839 -0.5839 -0.5839 -0.3585 2.3565

Coefficients:

            Estimate Std. Error z value Pr(>|z|) (Intercept) -1.68271 0.02363 -71.20 <2e-16 *** TO1 -1.02959 0.09012 -11.43 <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: 12987  on 15809  degrees of freedom
Residual deviance: 12819  on 15808  degrees of freedom
AIC: 12823

Number of Fisher Scoring iterations: 5


> setwd("P:/Work in Progress/Haibo/Hans")
>
> Lease=read.csv("lease.csv", header=TRUE)
> Lease$ET <- factor(Lease$EarlyTermination)
> SICCode=factor(Lease$SIC.Code)
> Lease$TO=factor(Lease$TenantHasOption)
> Lease$LO=factor(Lease$LandlordHasOption)
> Lease$TEO=factor(Lease$TenantExercisedOption)
>
> RegA=glm(ET~1+TO,
+ family=binomial(link=logit), data=Lease, weights=PortionSF) Warning message: non-integer #successes in a binomial glm! in: eval(expr, envir, enclos)
> summary(RegA)
Call: glm(formula = ET ~ 1 + TO, family = binomial(link = logit), data = Lease, weights = PortionSF) Deviance Residuals: Min 1Q Median 3Q Max -0.055002 -0.003434 0.000000 0.000000 0.120656 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -1.120 2.618 -0.428 0.669 TO1 -1.570 9.251 -0.170 0.865 (Dispersion parameter for binomial family taken to be 1) Null deviance: 1.0201 on 9302 degrees of freedom Residual deviance: 0.9787 on 9301 degrees of freedom AIC: 4 Number of Fisher Scoring iterations: 5 ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Received on Tue Aug 09 07:12:48 2005

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