title: Observer agreement for timed-event sequential data: a comparison of time-based and event-based algorithms.
abstract: Observer agreement is often regarded as the sine qua non of observational research. Cohen's kappa is a widely used index and is appropriate when discrete entities-such as a turn-of-talk or a demarcated time interval-are presented to pairs of observers to code. kappa-like statistics and agreement matrices are also used for the timed-event sequential data produced when observers first segment and then code events detected in the stream of behavior, noting onset and offset times. Such kappas are of two kinds: time-based and event-based. Available for download is a computer program (OASTES; Observer Agreement for Simulated Timed Event Sequences) that simulates the coding of observers of a stated accuracy and then computes agreement statistics for two time-based kappas (with and without tolerance) and three event-based kappas (one implemented in The Observer, one in INTERACT, and one in GSEQ). On the basis of simulation results presented here, and due to the somewhat different information provided by each, the reporting of both a time-based and an event-based kappa is recommended.
authors.affiliation: Department of Psychology, Georgia State University, P.O. Box 5010, 30302-5010, Atlanta, GA. bakeman@gsu.edu.
authors.forename: Roger
authors.initials: R
authors.lastname: Bakeman
authors.affiliation: University of Barcelona, Barcelona, Spain.
authors.forename: Vicenç
authors.initials: V
authors.lastname: Quera
authors.affiliation: Second University of Naples, Caserta, Italy.
authors.forename: Augusto
authors.initials: A
authors.lastname: Gnisci
mesh_terms: D000465:Algorithms; D001525:Behavioral Sciences / Q000295:instrumentation / Q000706:statistics & numerical data; D003198:Computer Simulation; D006801:Humans; D019370:Observation; D013997:Time Factors