Observer agreement for event sequences: methods and software for sequence alignment and reliability estimates.
When sequences of discrete events, or other units, are independently coded by two coders using a set of mutually exclusive and exhaustive codes, but the onset times for the codes are not preserved, it is often unclear how pairs of protocols should be aligned. Yet such alignment is required before Cohen's kappa, a common agreement statistic, can be computed. Here we describe a method--based on the Needleman and Wunsch (1970) algorithm originally devised for aligning nucleotide sequences--for optimally aligning such sequences; we also offer the results of a simulation study of the behavior of alignment kappa with a number of variables, including number of codes, varying degrees of observer accuracy, sequence length, code variability, and parameters governing the alignment algorithm. We conclude that (1) under most reasonable circumstances, observer accuracies of 90% or better result in alignment kappas of .60 or better; (2) generally, alignment kappas are not strongly affected by sequence length, the number of codes, or the variability in the codes' probability; (3) alignment kappas are adversely affected when missed events and false alarms are possible; and (4) cost matrices and priority orders used in the algorithm should favor substitutions (i.e., disagreements) over insertions and deletions (i.e., missed events and false alarms). Two computer programs were developed: Global Sequence Alignment, or GSA, for carrying out the simulation study, and Event Alignment, or ELign, a user-oriented program that computes alignment kappa and provides the optimal alignment given a pair of event sequences.
Quera
Vicenç
V
Departamento de Metodología de las Ciencias del Comportamiento, Universidad de Barcelona, Barcelona, Spain. vquera@ub.edu
Bakeman
Roger
R
Gnisci
Augusto
A
D000465:Algorithms; D006801:Humans; D008016:Life Change Events; D008960:Models, Psychological; D015588:Observer Variation; D011584:Psychology / Q000379:methods / Q000706:statistics & numerical data*; D012984:Software