Jef Vlegels
2010-Aug-30 15:17 UTC
[R] 'mgcv' package, problem with predicting binomial (logit) data
Dear R-help list,
I?m using the mgcv package to plot predictions based on the gam function.
I predict the chance of being a (frequent) participant at theater plays vs.
not being a participant by age.
Because my outcome variable is dichotomous, I use the binomial family with
logit link function.
Dataset in attachment, code to read it in R:
data <- read.spss("pas_r.sav")
attach(data)
In a first step I use ?gam? to model my data and ?predict? to calculate and
plot the predicted values, this all works fine.
My code looks like this:
test <- gam(participant ~ s(age,fx=FALSE,bs='cr'),
family=binomial(logit))
summary(test)
plot(test, shade=TRUE)
gam.check(test)
test.pred <- predict(test,newdata=data,se.fit=TRUE,type='response',
na.action=na.omit)
I1<-order(age)
plot(age[I1], test.pred$fit[I1],lty=1, type="l")
lines(age[I1],test.pred$fit[I1]+2*M1pred$se[I1],lty=2)
lines(age[I1],test.pred$fit[I1]-2*M1pred$se[I1],lty=2)
plot(age[I1], test.pred$fit[I1] , type="l")
I a second step, I want to calculate a similar model, but only for
respondents with a certain characteristic. For example, in this case, only
for male respondents.
I use a code that looks like this:
participant_male <- participant[gender=="male"]
age_male <- age[gender=="male"]
test2<-gam(participant_male ~ s(age_male, fx=FALSE, bs="cr"),
family=binomial(logit), na.action=na.omit)
summary(test2)
plot(test2, shade=TRUE)
I get a nice smoother function in this plot, like I expected.
Then, when I want to plot the predicted values, I use a code that looks like
this:
Test2.pred <- predict(test5,se.fit=TRUE, type="response")
I1<-order(age_male)
plot(age_male[I1], test2.pred$fit[I1],lty=1)
This last plot, of the predictions, is not what I expect. It?s just a random
scatterplot, not what I would expect from the smoother plot. Does anybody
know what I did wrong?
Thanks in advance,
Jef Vlegels
Jef Vlegels
Ghent University - Department of Sociology
Korte Meer 3, B-9000 Gent, Belgium
Tel:? 09 264 8343
www.psw.UGent.be/sociologie
Jef Vlegels
2010-Aug-30 15:44 UTC
[R] 'mgcv' package, problem with predicting binomial (logit) data
There was a problem with the data in attachment, here is a better version.
Use something like:
data <- read.table("pas_r.txt",header=TRUE,sep=";")
to read it.
Thanks,
Jef
-----Original Message-----
From: David Winsemius [mailto:dwinsemius at comcast.net]
Sent: maandag 30 augustus 2010 17:22
To: Jef Vlegels
Subject: FYI offlist Re: [R] 'mgcv' package, problem with predicting
binomial (logit) data
On Aug 30, 2010, at 11:17 AM, Jef Vlegels wrote:
> Dear R-help list,
>
> I'm using the mgcv package to plot predictions based on the gam
> function.
>
> I predict the chance of being a (frequent) participant at theater
> plays vs.
> not being a participant by age.
> Because my outcome variable is dichotomous, I use the binomial
> family with
> logit link function.
>
> Dataset in attachment, code to read it in R:
Nope. .sav files are not accepted by the mail-server. See the Posting
Guide. (.txt and .pdf are the safest formats)
> data <- read.spss("pas_r.sav")
> attach(data)
>
> In a first step I use 'gam' to model my data and 'predict'
to
> calculate and
> plot the predicted values, this all works fine.
> My code looks like this:
>
> test <- gam(participant ~ s(age,fx=FALSE,bs='cr'),
> family=binomial(logit))
> summary(test)
> plot(test, shade=TRUE)
> gam.check(test)
> test.pred <-
predict(test,newdata=data,se.fit=TRUE,type='response',
> na.action=na.omit)
> I1<-order(age)
> plot(age[I1], test.pred$fit[I1],lty=1, type="l")
> lines(age[I1],test.pred$fit[I1]+2*M1pred$se[I1],lty=2)
> lines(age[I1],test.pred$fit[I1]-2*M1pred$se[I1],lty=2)
> plot(age[I1], test.pred$fit[I1] , type="l")
>
> I a second step, I want to calculate a similar model, but only for
> respondents with a certain characteristic. For example, in this
> case, only
> for male respondents.
> I use a code that looks like this:
>
> participant_male <- participant[gender=="male"]
> age_male <- age[gender=="male"]
>
> test2<-gam(participant_male ~ s(age_male, fx=FALSE, bs="cr"),
> family=binomial(logit), na.action=na.omit)
> summary(test2)
> plot(test2, shade=TRUE)
>
> I get a nice smoother function in this plot, like I expected.
> Then, when I want to plot the predicted values, I use a code that
> looks like
> this:
>
> Test2.pred <- predict(test5,se.fit=TRUE, type="response")
> I1<-order(age_male)
> plot(age_male[I1], test2.pred$fit[I1],lty=1)
>
> This last plot, of the predictions, is not what I expect. It's just
> a random
> scatterplot, not what I would expect from the smoother plot. Does
> anybody
> know what I did wrong?
>
> Thanks in advance,
> Jef Vlegels
>
> Jef Vlegels
> Ghent University - Department of Sociology
> Korte Meer 3, B-9000 Gent, Belgium
> Tel: 09 264 8343
> www.psw.UGent.be/sociologie
>
>
> ______________________________________________
> 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.
David Winsemius, MD
West Hartford, CT
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