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Hallo to all I am trying to plot the learning curves of two groups of participants using the lineplot.CI() function. Since there are 30 levels on my x-axix, the resulting curves is kind of fragmented and not really...
Hi all I am using the bam function of the mgcv package to model behavioral data of a learning experiment. To model individual variation in learning rate, I am testing models with (a) by-participant random intercepts of trial, (b...
Sorry for that, I was trying to keep my question short. lineplot.CI(blck, perf, group = cnd, xlab="Block", ylab="% Optimal Responses", cex.leg=1.2, x.leg = 18, y.leg=0.4, err.width=0.05, pch = c(15...
Dear Professor Wood, Thank you for taking the time to fix the problem. Best, Fotis On Thu, Sep 22, 2016 at 4:25 PM, Simon Wood <simon.wood at bath.edu> wrote: > Hi Fotis, > > Thanks for the report, and sending...
Sorry for that, I was only trying to be short. data<-read.table("2_3_blocksof10.txt", header=T) sbj<-as.factor(data$Subj) cnd<-as.factor(data$Cond) blck<-as.factor(data$Block) perf<-data$Perf dat<-data.frame...
Dear Prof. Wood, Thank you for your reply! Best, Fotis On Wed, May 18, 2016 at 12:05 PM, Simon Wood <simon.wood at bath.edu> wrote: > Dear Fotis, > > The test is a randomization test, based on comparing differences of...
It's much more elegant if I set the 'type' parameter to "p" in lineplot.CI... Thank you, that was really helpful!!!! --- ???? ???., 27/10/10, ?/? Thomas Levine <thomas.levine at gmail.com> ??????: > ???: Thomas Levine <thomas.levine at gmail.com> > ????: Re...
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...
Dear Prof. Wood Thank you, again, for your immediate response. Best, Fotis On Mon, May 23, 2016 at 4:32 PM, Simon Wood <simon.wood at bath.edu> wrote: > Q1: It looks like the model is not fully identifiably given...
Hello all I am using bam for a mixec-effects logistic regression model: b0<-bam(acc~ 1 + igc + s(ctrial, by=igc) + s(sbj, bs="re") + s(ctrial, sbj, bs="re") , data=data, family=binomial) >summary(b0) Family: binomial Link...
Hallo all I am using a gam model for my data. m2.4<-bam(acc~ 1 + igc + s(ctrial, by=igc) + shape + s(ctrial, by=shape) + s(ctrial, sbj, bs = "fs", m = 1) , data=data, family=binomial) igc codes condition...
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...
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