Dear colleagues, I’ve written a short note relating to a simulation I ran to clarify my muddy thinking about the effects of bias (towards match or mismatch) in face matching experiments and the way that principal components analysis separates match and mismatch items into different components. I can’t see it making a published paper but I figure others may find it useful, so I’ve put it up on psyarxiv: https://psyarxiv.com/f2a9j Bottom line: when participants vary in bias and ability independently, PCA tends to separate match and mismatch trials, especially after varimax rotation.

The (not very elegant) matlab simulation code is on OSF, linked from the paper.

Comments welcome, to me rather than the whole list.

 

Peter

 

 

Peter Hancock (he/him)
Professor
Psychology, School of Natural Sciences
University of Stirling
FK9 4LA, UK
phone 01786 467675
http://rms.stir.ac.uk/converis-stirling/person/11587

@pjbhancock

Latest paper:
Simulated automated facial recognition systems as decision-aids in forensic face matching tasks.
https://psycnet.apa.org/doiLanding?doi=10.1037%2Fxge0001310

My messages may arrive outside of the working day but this does not imply any expectation that you should reply outside of your normal working hours. If you wish to respond, please do so when convenient.