Dear Thierry, Dear all,
Many thanks for your replies.
Le jeudi 16 février 2023 à 10:39:34 UTC+1, Thierry Onkelinx
<thierry.onkel...@inbo.be> a écrit :
Dear Sacha,
use glm() in this case. I'd rather code the covariable as TRUE / FALSE or as a
factor.
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.onkel...@inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be
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To call in the statistician after the experiment is done may be no more than
asking him to perform a post-mortem examination: he may be able to say what the
experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
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that a reasonable answer can be extracted from a given body of data. ~ John
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Op za 11 feb. 2023 om 18:35 schreef varin sacha via R-help
<r-help@r-project.org>:
> Dear R-experts,
>
> I am trying to fit a GAM with 2 binary predictors (variables coded 0,1). I
> guess I cannot just smooth binary variables. By the way I code them as
> 0=no,1=yes, then mgcv will think those variables are numeric.
> I have tried to change 0 and 1 in no and yes. It does not work.
> How to solve my problem. Here below my toy example. Many thanks.
>
> Best,
> Sacha
>
> ########################
> y=c(0.02,0.1,0.04,0.07,0.09,0.1,0.054,0.076,0.0897,0.09,0.1,0.86,0.74,0.53,0.35,0.67,0.63,0.95,0.72,0.85)
> x1=c(1,0,0,1,1,0,0,1,0,1,1,1,0,1,0,0,0,1,0,0)
> x2=c(0,0,1,1,0,1,1,0,0,1,1,1,0,0,1,0,0,1,1,0)
>
> library(mgcv)
> reg = gam(y ~ s(x1) +s(x2), family=binomial(link="logit"))
> summary(reg)
> ########################
>
>
>
> ########################
> y=c(0.02,0.1,0.04,0.07,0.09,0.1,0.054,0.076,0.0897,0.09,0.1,0.86,0.74,0.53,0.35,0.67,0.63,0.95,0.72,0.85)
> x1=c("yes","no","no","yes","yes","no","no","yes","no","yes","yes","yes","no","yes","no","no","no","yes","no","no")
> x2=c("no","no","yes","yes","no","yes","yes","no","no","yes","yes","yes","no","no","yes","no","no","yes","yes","no")
> library(mgcv)
> reg = gam(y ~ s(x1) +s(x2), family=binomial(link="logit"))
> summary(reg)
> ########################
>
> ______________________________________________
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>
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