Analysis of signal detection data

This situation is well described and most appropriately analyzed by the 
use of GEE methods.

Mike Lawrence wrote:

Yet another query on whether traditional stats employed in psychology
might be improved by mixed effects modelling...
[diagnostic accuracy v. gold standard]

As I understand it, GEE can be seen as an approximate method related to 
approaches such as quasi-likelihood, though there may be cases where its 
underlying model is closer to the true state of what you are actually 
looking at.  So, a GLMM may better -- I'm more familiar with SEM/ 
graphical models for this type of setup, in that they are more flexible
eg diagnosis where there is no gold standard diagnosis to compare to, 
mixture models for task difficulty... 
These will usually have a "full likelihood" GLMM underlying them, or some 
type of approximation eg Browne's WLS seen in Lisrel/MX.

Just 2c, David Duffy.

| David Duffy (MBBS PhD)                                         ,-_|\
| email: davidD at qimr.edu.au  ph: INT+61+7+3362-0217 fax: -0101  /     *
| Epidemiology Unit, Queensland Institute of Medical Research   \_,-._/
| 300 Herston Rd, Brisbane, Queensland 4029, Australia  GPG 4D0B994A v