[R] model formula
Eik Vettorazzi
E.Vettorazzi at uke.uni-hamburg.de
Thu Aug 11 19:57:52 CEST 2011
Am 11.08.2011 17:39, schrieb Uwe Ligges:
>
>
> On 11.08.2011 17:27, Bond, Stephen wrote:
>> Hello useRs,
>>
>> Pls help with removing a single interaction term from a formula:
>>
>> summary(
>> glm.turn.2<-
>> glm(cbind(turn.cnt,tot.cnt-turn.cnt)~sn+poly(relAge,2,raw=T)+termfac+rate:termfac,data=fix,
>>
>> family="quasibinomial")
>> )
>>
>> Gives
>>
>> Coefficients:
>> Estimate Std. Error t value Pr(>|t|)
>> (Intercept) -7.028467 0.106002 -66.305< 2e-16 ***
>> snFeb 0.156963 0.023660 6.634 3.27e-11 ***
>> snMar 0.317540 0.022883 13.876< 2e-16 ***
>> snApr 0.526084 0.022004 23.908< 2e-16 ***
>> snMay 1.026710 0.020347 50.460< 2e-16 ***
>> snJun 0.841044 0.021318 39.452< 2e-16 ***
>> snJul 0.668790 0.022530 29.685< 2e-16 ***
>> snAug 0.544267 0.022580 24.104< 2e-16 ***
>> snSep 0.389667 0.023363 16.679< 2e-16 ***
>> snOct 0.351294 0.023586 14.894< 2e-16 ***
>> snNov 0.391464 0.024057 16.272< 2e-16 ***
>> snDec -0.373369 0.028755 -12.985< 2e-16 ***
>> poly(relAge, 2, raw = T)1 2.952887 0.067455 43.776< 2e-16 ***
>> poly(relAge, 2, raw = T)2 -1.783907 0.064074 -27.841< 2e-16 ***
>> termfac2 -0.681719 0.128571 -5.302 1.14e-07 ***
>> termfac3 -1.032416 0.146396 -7.052 1.77e-12 ***
>> termfac4 -1.267011 0.108940 -11.630< 2e-16 ***
>> termfac5 -1.009922 0.213129 -4.739 2.15e-06 ***
>> termfac6 3.300301 0.203465 16.221< 2e-16 ***
>> termfac1:rate 0.012274 0.019895 0.617 0.537
>> termfac2:rate 0.121724 0.013472 9.036< 2e-16 ***
>> termfac3:rate 0.175232 0.018987 9.229< 2e-16 ***
>> termfac4:rate 0.197726 0.005787 34.164< 2e-16 ***
>> termfac5:rate 0.145622 0.027295 5.335 9.56e-08 ***
>> termfac6:rate -0.362379 0.025261 -14.345< 2e-16 ***
>>
>> and I would like to remove the termfac1:rate interaction. Is there a
>> way to do that?
>> Thank you
>
> And what do you want to do with the observations with termfac=1 then?
> Ignore? Also move to the Intercept?
Actually they are already in the Intercept because of the treatment
contrasts. The crucial part in the glm formula above is
termfac+rate:termfac
which specifies intercepts deviating from termfac1 level and slopes for
every level of termfac. A dummy coding for different slopes should work,
since the slopes are independently modelled and tested against 0.
>
> Uwe Ligges
>
>
>
>>
>> Stephen Bond
>>
>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
--
Eik Vettorazzi
Institut für Medizinische Biometrie und Epidemiologie
Universitätsklinikum Hamburg-Eppendorf
Martinistr. 52
20246 Hamburg
T ++49/40/7410-58243
F ++49/40/7410-57790
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