Functions for traditional and multilevel approaches to signal detection theory.
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.
Wright
Daniel B
DB
Florida International University, Miami, Florida 33265, USA. dwright@fiu.edu
Horry
Ruth
R
Skagerberg
Elin M
EM
D000465:Algorithms; D003627:Data Interpretation, Statistical; D006801:Humans; D017603:Signal Detection, Psychological; D012984:Software