I am working with n-back paradigm. Participants were presented 0-back, 1-back, 2-back and 3-back conditions three times. Therefore, there are 3 trials for each n-back condition in my experiment for every participant. Participants were required to press the left button if they see a target letter, and right button if they see a non-target letter, based on the instructed condition. There are 10 target and 20 non-target letters in a single n-back condition. So, for example for 0-back condition total number of signal trial is 30, and total number of noise trial is 60. I want to learn whether participants distinguish target letters from non-target letters and also whether they have a bias on responding as target. First of all, I've calculated d' and c, as Stanislaw and Todorov suggested, by using excel commands. What I've see when I've finished my calculation is that, i.e., -0,181, -0,784 values of d' and so on. Generally, d' values are negative. Negative values are very bad for me. Because this means that participants cannot distinguish target and non-target letters. So, they've press the buttons by chance. In addition, before I've made my calculation, I've made a correction which is dubbed loglinear correction, as Hautus suggested, to all of my hits and false alarms. The dissappointing point for me is that I've found a significant effect of condition (i.e., as the n-back condition gets harder, the number of deteceted target letters has decrease). I wonder if is it possible to conduct a signal detection analysis to this type of an experimental design?
Dear Ilgim,
I expect that the problem can be addressed. To give you a serious suggestion requires to know more details about the work you are doing and its aims. Please, send me relevant papers (at least reference to them) and a (possibly informal) description of the aim of your project.
best regards Miroslav Karny, [email protected]
Hello Ilgim,
Signal detection tasks require 'Yes / No' responses. If you can arrange your experimental protocol so that subjects have to indicate whether the target letter was in a certain position or not, then you have data suitable for a SDT analysis.
Regards,
Michael
- Badges
- Science topic
- Similar topics
- Medicine
- Physiology
- Biosignals
- Biomedical Signal Processing
- Statistical Analysis