Analysis of signal detection data
Thanks all for your responses and input! :O) Cheers, Mike -- Mike Lawrence Graduate Student Department of Psychology Dalhousie University Looking to arrange a meeting? Check my public calendar: http://tr.im/mikes_public_calendar ~ Certainty is folly... I think. ~
On Mon, Nov 15, 2010 at 1:17 PM, Ed Merkle <edgar.merkle at wichita.edu> wrote:
Mike,
I would add the following paper, which discusses Bayesian SDT models.
Rouder's website may have software to estimate the models.
@ARTICLE{RouLu05,
?author = {J. N. Rouder and J. Lu},
?title = {An introduction to {B}ayesian hierarchical models with an
application in the theory of signal detection},
?journal = {Psychonomic Bulletin and Review},
?year = {2005},
?volume = {12},
?pages = {573-604}
}
Ed
--
Ed Merkle, PhD
Assistant Professor
Department of Psychology
Wichita State University
Wichita, KS, USA 67260
http://psychology.wichita.edu/merkle
-----Original Message-----
From: r-sig-mixed-models-bounces at r-project.org on behalf of Mike Lawrence
Sent: Sun 11/14/2010 9:58 PM
To: r-sig-mixed-models at r-project.org
Subject: [R-sig-ME] Analysis of signal detection data
I know mixed effects modelling can handle binomially distributed
error, but is there any way to handle this sort of signal detection
data? My first thought is that glmmer with 4 categories corresponding
to the hit, miss, false alarm, and correction categorization of
responses, but I don't immediately see how this would properly connect
the hit-vs-miss data to reflect a hit rate and the
false-alarm-vs-correct-rejection data to reflect a FA rate.
Thoughts?
Mike
--
Mike Lawrence
Graduate Student
Department of Psychology
Dalhousie University
Looking to arrange a meeting? Check my public calendar:
http://tr.im/mikes_public_calendar
~ Certainty is folly... I think. ~
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