# bigglm binomial negative fitted value

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## bigglm binomial negative fitted value

 Hi, there Since glm cannot handle factors very well. I try to use bigglm like this: logit_model <- bigglm(responser~var1+var2+var3, data, chunksize=1000, family=binomial(), weights=~trial, sandwich=FALSE) fitted <- predict(logit_model, data) only var2 is factor, var1 and var3 are numeric. I expect fitted should be a vector of value falls in (0,1) However, I get something like this: str(fitted)  num [1:260617, 1] -0.0564 -0.0564 -0.1817 -0.1842 -0.1852 ...  - attr(*, "dimnames")=List of 2   ..\$ : chr [1:260617] "1" "2" "3" "4" ...   ..\$ : NULL Anyone can help on this case? Thank you in advance. Best, --Yue ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: bigglm binomial negative fitted value

 On Fri, Jun 1, 2012 at 1:17 AM, Yue Guan <[hidden email]> wrote: > Hi, there > > Since glm cannot handle factors very well. I try to use bigglm like this: > > logit_model <- bigglm(responser~var1+var2+var3, data, chunksize=1000, > family=binomial(), weights=~trial, sandwich=FALSE) > > fitted <- predict(logit_model, data) > > only var2 is factor, var1 and var3 are numeric. > > I expect fitted should be a vector of value falls in (0,1) > > However, I get something like this: > str(fitted) >  num [1:260617, 1] -0.0564 -0.0564 -0.1817 -0.1842 -0.1852 ... >  - attr(*, "dimnames")=List of 2 >  ..\$ : chr [1:260617] "1" "2" "3" "4" ... >  ..\$ : NULL > As the help says, the default is predictions of the linear predictor. To get predictions of the probability, use type="response"    -thomas -- Thomas Lumley Professor of Biostatistics University of Auckland ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: bigglm binomial negative fitted value

 Thank you very much. I do overlook something..... On Thu, May 31, 2012 at 5:20 PM, Thomas Lumley <[hidden email]> wrote: > On Fri, Jun 1, 2012 at 1:17 AM, Yue Guan <[hidden email]> wrote: >> Hi, there >> >> Since glm cannot handle factors very well. I try to use bigglm like this: >> >> logit_model <- bigglm(responser~var1+var2+var3, data, chunksize=1000, >> family=binomial(), weights=~trial, sandwich=FALSE) >> >> fitted <- predict(logit_model, data) >> >> only var2 is factor, var1 and var3 are numeric. >> >> I expect fitted should be a vector of value falls in (0,1) >> >> However, I get something like this: >> str(fitted) >>  num [1:260617, 1] -0.0564 -0.0564 -0.1817 -0.1842 -0.1852 ... >>  - attr(*, "dimnames")=List of 2 >>  ..\$ : chr [1:260617] "1" "2" "3" "4" ... >>  ..\$ : NULL >> > > As the help says, the default is predictions of the linear predictor. > To get predictions of the probability, use type="response" > >   -thomas > > -- > Thomas Lumley > Professor of Biostatistics > University of Auckland ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.