[R] itsadug:: plot_smooth and plot_diff

[Fotis Fotiadis]

Dear Bert,
Thank you for your response

Best,
Fotis

On Sun, Jun 12, 2016 at 5:50 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote:

> To be clear, I know nothing about bam; I just wanted to correct a
> statistical error:
>
> "Since the 95% confidence intervals overlap, I would assume that there is
> no
> difference in accuracy between the two conditions."
>
> That is false. You need to look at a CI for the difference.
>
> As you appear to be confused about the statistical issues, I suggest
> you post on a statistical site like stats.stackexchange.com or consult
> a local statistician.
>
> Cheers,
> Bert
>
>
> Bert Gunter
>
> "The trouble with having an open mind is that people keep coming along
> and sticking things into it."
> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>
>
> On Sun, Jun 12, 2016 at 7:03 AM, Fotis Fotiadis <fotisfotiadis at gmail.com>
> wrote:
> > Hi all
> >
> > I am using bam to analyse the data from my experiment.
> > It's a learning experiment, "acc" denotes accuracy and "cnd" denotes a
> > within-subjects variable (with two levels, "label" and "ideo")."Ctrial"
> is
> > centered trial (ranging from 1 to 288).
> >
> > The model is:
> > bam(acc~ 1 + cnd + s(ctrial) + s(ctrial, sbj, bs = "fs", m = 1),
> data=data,
> > family=binomial)
> >
> > The model doesn't include two different smooths (one for each condition)
> > since including two smooths does not result to a more parsimonious model,
> > according to following model comparison:
> >> compareML(m0.2, m1.2)
> > m0.2: acc ~ 1 + cnd + s(ctrial) + s(ctrial, sbj, bs = "fs", m = 1)
> >
> > m1.2: acc ~ 1 + cnd + s(ctrial, by = cnd) + s(ctrial, sbj, bs = "fs",
> >     m = 1)
> >
> > Chi-square test of fREML scores
> > -----
> >   Model    Score Edf Chisq    Df   p.value Sig.
> > 1  m0.2 10183.31   6
> > 2  m1.2 10173.33   8 9.975 2.000 4.654e-05  ***
> >
> > AIC difference: -2.16, model m0.2 has lower AIC.
> >
> >
> > So, I'm trying to assess if there's a difference in accuracy between the
> > two conditions.
> >
> > When using the plot_smooth function, the model predictions are the ones
> > shown in Fig.1.
> > The code used is:
> > plot_smooth(fm, view="ctrial",
> > cond=list(cnd="pseudo"),main="Model",xaxt="n",
> > xlab="Trial",ylab="Proportion Correct", lwd=2, las=2, rm.ranef=TRUE,
> > rug=FALSE, shade=T, col="red" )
> > plot_smooth(fm, view="ctrial", cond=list(cnd="ideo"), xaxt="n",
> > rm.ranef=TRUE, rug=FALSE, shade=T, col="blue", add=T , lty=2, lwd=2)
> > legend(x=0.8, y=1.5,legend=c('Label', 'Ideogram'),col=c('red', 'blue'),
> > lty=c(1,2), bty="n", lwd=2)
> >
> > Since the 95% confidence intervals overlap, I would assume that there is
> no
> > difference in accuracy between the two conditions.
> >
> > I am also using plot_diff to directly plot the difference:
> > plot_diff(fm, view="ctrial",comp=list(cnd=c("pseudo", "ideo")),
> > transform.view=dnrmlz,rm.ranef=T)
> > (dnrmlz is a simple function to de-normalize trial)
> >
> > The output of the function is:
> > Summary:
> > * ctrial : numeric predictor; with 100 values ranging from -1.725936 to
> > 1.725936.
> > * sbj : factor; set to the value(s): aggmpo96. (Might be canceled as
> random
> > effect, check below.)
> > * NOTE : The following random effects columns are canceled: s(ctrial,sbj)
> >
> > * Note: x-values are transformed.
> >             Significant
> > 1 0.759461 - 288.240539
> >
> > So, it seems that accuracy in the label condition is higher compared to
> the
> > ideo condition throughout the experiment.
> > This result seems to contradict the previous one.
> >
> > I am obviously misinterpreting something.
> > Any ideas on what am I doing wrong?
> >
> > Thank you in advance for your time,
> > Fotis
> >
> >
> >
> >
> >
> >
> >
> > --
> > PhD Candidate
> > Department of Philosophy and History of Science
> > University of Athens, Greece.
> > http://users.uoa.gr/~aprotopapas/LLL/en/members.html#fotisfotiadis
> >
> > Notice: Please do not use this account for social networks invitations,
> for
> > sending chain-mails to me, or as it were a facebook account. Thank you
> for
> > respecting my privacy.
> >
> > <
> https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail
> >
> > Virus-free.
> > www.avast.com
> > <
> https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail
> >
> > <#DDB4FAA8-2DD7-40BB-A1B8-4E2AA1F9FDF2>
> >
> > ______________________________________________
> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > 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.
>



-- 
PhD Candidate
Department of Philosophy and History of Science
University of Athens, Greece.
http://users.uoa.gr/~aprotopapas/LLL/en/members.html#fotisfotiadis

Notice: Please do not use this account for social networks invitations, for
sending chain-mails to me, or as it were a facebook account. Thank you for
respecting my privacy.

	[[alternative HTML version deleted]]