From: Prof Brian Ripley <ripley_at_stats.ox.ac.uk>

Date: Tue 09 Aug 2005 - 16:24:02 EST

Date: Tue 09 Aug 2005 - 16:24:02 EST

On Mon, 8 Aug 2005, Haibo Huang wrote:

> 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.
*

Weights are case weights in a binomial GLM, that is w_i means `I have w_i of these'. Do check out the theory in MASS (the book) or Nelder & McCullagh. There are some circumstances when fractional weights make sense (when this doing something other than fitting a glm, e.g. part of a `mixture of experts' model) but they are unusual, hence the warning.

*>
*

> 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
*

-- Brian D. Ripley, ripley@stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ 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.htmlReceived on Tue Aug 09 16:30:40 2005

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