Dear Bruno,
I'm sure you can find the answers to your questions in
Macmillan, N.A., & Creelman, C. D. (2005). Detection Theory. A User's
Guide. 2nd edition. Mawah: Erlbaum.
Could you give some more details about the stimuli you want to use, then
it will be easier to point out studies related to your questions.
Just a few general notes:
I'd suggest considering the area under the ROC curve as a measure of
sensitivity because it relies on fewer assumptions than d' (Macmillan &
Creelman discuss this in detail). The area under the ROC curve is widely
used in medical decision making (e.g., a radiologist looks at mammograms
and classifies them as normal, benign, probably benign, suspicious, or
malignant), so it might be interesting to consider this body of
literature. Specifically, models have been formulated which take into
account the data from several observers (for a recent review see
Obuchovski, N. A. (2007). New methodological tools for multiple-reader
ROC studies. Radiology, 243, 10-12). Alternatively, Macmillan and
Creelman discuss the pooling of observations.
Kind regards,
Daniel