[R] glm package - Negative binomial regression model - Error

[Thierry Onkelinx]

Dear Paula,

There are probably missing observations in your data set. Read the
na.action part of the glm help file. na.exclude is most likely what you are
looking for.

Best regards,


ir. Thierry Onkelinx
Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx at inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be

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2018-02-26 2:07 GMT+01:00 Paula Couto <paulaveronica at gmail.com>:

> HI there
>
> I am running this model in negative binomial regression, using glm.
> I had no problems with running the model with a set of data, but now that
> i'm trying to run if for new one.  I always have this same error when
> running the regression:
>
> >
> > #Run Regression
> >     x=cbind(factor2ind(d$year),factor2ind(d$month_week))
> >
> >     out<- glm(cbind(influenza, n_sample) ~ x, family=quasibinomial,
> > data=d)
> >
> >     d$prop<-out$fitted.values
>
> Error in `$<-.data.frame`(`*tmp*`, prop, value = c(0.0486530542835839,  :
>   replacement has 208 rows, data has 365
>
> >     d$n_p1<-d$prop*d$factor*10
> >
> >     obs<-aggregate(d$prop, by = list(d$month_week), FUN=summary)
> >     pred<-aggregate(d$n_p1, by = list(d$month_week), FUN=summary)
> >
>
> By the way, I previously prepared the data set  and defined that:
>        d$factor<-sapply(d$year,f)
> >         d$n_sample<-(d$n_muestras*d$factor*10)
> >         d$prop<-(d$influenza/d$n_sample)
>
> But I still don't understand why it keeps saying that dataframe has less
> replacements than rows.
> Could anybody help me with this?
>  Many thankss!!!
> P
>
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