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), dataÚta,

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,

rugúLSE, shade=T, col="red" )

plot_smooth(fm, view="ctrial", cond=list(cnd="ideo"), xaxt="n",

rm.ranef=TRUE, rugúLSE, 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.

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