[R] psychometric functions

Doran, Harold HDoran at air.org
Thu Aug 21 15:35:32 CEST 2008


I don't know that you would be too far away from being able to use R
from doing this. I haven't thought about this model, but if you could
write out the likelihood, you *might* be able to use the MML procedures
that is used for similar psychometric functions in ltm, which I think
uses optim()

> -----Original Message-----
> From: r-help-bounces at r-project.org 
> [mailto:r-help-bounces at r-project.org] On Behalf Of Mario Maiworm
> Sent: Thursday, August 21, 2008 9:16 AM
> To: r-help at r-project.org
> Subject: Re: [R] psychometric functions
> 
> Thank you harold. Hmm thats bad news. I will have a look at 
> the LTM package but right now I feel like I should lean back 
> and use matlab, and then get the fit results into R for 
> further analyses...
> mario
> 
> 
> __________________________________________________________________
> 
> Mario Maiworm
> Biological Psychology and Neuropsychology University of 
> Hamburg Von-Melle-Park 11
> D-20146 Hamburg
> 
> Phone: +49 40 42838 8265
> Fax: +49 40 42838 6591
> 
> http://bpn.uni-hamburg.de/Maiworm_e.html
> http://cinacs.org
> __________________________________________________________________
> 
> >>> -----Original Message-----
> >>> From: Doran, Harold [mailto:HDoran at air.org]
> >>> Sent: Thursday, August 21, 2008 2:40 PM
> >>> To: Mario Maiworm; r-help at r-project.org
> >>> Subject: RE: [R] psychometric functions
> >>> 
> >>> I am pretty certain a function for this model does not exist. Jan 
> >>> Deleeuw or Dimitris Rizopolous may suggest otherwise. There is a 
> >>> package for a model that would allow for the lower 
> asymptote of the 
> >>> function to be > 0; it does not however, allow the upper 
> asymptote 
> >>> to vary from 1 (well, it tends to 1) and this is in the 
> ltm package.
> >>> 
> >>> 
> >>> > -----Original Message-----
> >>> > From: r-help-bounces at r-project.org 
> >>> > [mailto:r-help-bounces at r-project.org] On Behalf Of Mario Maiworm
> >>> > Sent: Thursday, August 21, 2008 7:05 AM
> >>> > To: r-help at r-project.org
> >>> > Subject: [R] psychometric functions
> >>> >
> >>> > Hi,
> >>> > I want to fit some psychophysical data with cumulative 
> gaussians. 
> >>> > There is quite a convenient toolbox for matlab called 
> 'psignifit' 
> >>> > (formerly known as 'psychofit'). It allows the lower 
> bound of the 
> >>> > sigmoid to vary slightly from zero, aswell as the upper 
> bound to 
> >>> > vary from one. with these two free parameters, the 
> fitted function 
> >>> > is less sensitive to noisy data and outliers.
> >>> > Apart from advertising this toolbox I want to ask for 
> >>> > possibilities in R to fit psychometric functions, as I would 
> >>> > rather use R than matlab. Is there a comparable package 
> specific 
> >>> > for psychophysics in R? otherwise: which function would 
> be a good 
> >>> > choice? Can I have functionality equal to 'psignifit' 
> with glm() 
> >>> > from MASS. I would be grateful for some suggestions of 
> people who 
> >>> > have experience in sigmoid-fitting in R.
> >>> > Best,
> >>> > Mario.
> >>> >
> >>> >
> >>> > 
> __________________________________________________________________
> >>> >
> >>> > Mario Maiworm
> >>> > Biological Psychology and Neuropsychology University of Hamburg 
> >>> > Von-Melle-Park 11
> >>> > D-20146 Hamburg
> >>> >
> >>> > Phone: +49 40 42838 8265
> >>> > Fax: +49 40 42838 6591
> >>> >
> >>> > http://bpn.uni-hamburg.de/Maiworm_e.html
> >>> > http://cinacs.org
> >>> >
> >>> > ______________________________________________
> >>> > 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.
> >>> >
> 
> ______________________________________________
> 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.
> 



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