Functions for traditional and multilevel approaches to signal detection theory

Abstract

In the present article, functions written in the freeware R are presented that calculate several measures from traditional signal detection theory for each individual in a sample, along with summary statistics for the sample. Bias-corrected and accelerated bootstrap confidence intervals are also produced. Arguments are made for using an alternative approach-multilevel generalized linear models-and a function is presented for it. These functions are part of the R package sdtalt, which is available on the Comprehensive R Archive Network. Recent data from memory recognition studies are used to illustrate these functions. © 2009 The Psychonomic Society, Inc.