Using Generalized Linear Mixed Model for Signal Detection Theory
Wright et al. (2009, Behavior Research Methods; https://link.springer.com/article/10.3758/BRM.41.2.257) and others have suggested calculating signal detection theory indexes using multilevel generalized linear mixed modeling with probit as link function. The approach sounds very interesting and could be a great complement to GLMM approaches. I tried replicating example findings using GLMM in JASP (see https://rstudio-pubs-static.s3.amazonaws.com/480255_9baa652276b540d0a239188b9513a026.html#(6) or https://mvuorre.github.io/posts/2017-10-09-bayesian-estimation-of-signal-detection-theory-models/#example-data), but results are very different. Possibly the R code of Wright (mlmsdt) works different than what JASP uses. Is there another way to conduct SDT using GLMM in JASP and/or could it perhaps become a new JASP module?