# [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\$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,
> 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\$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,
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

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