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Observer agreement for event sequences: Methods and software for sequence alignment and reliability estimates

机译:事件序列的观察者协议:序列比对和可靠性估计的方法和软件

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摘要

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.
机译:当离散事件或其他单元的序列由两个编码器使用一组互斥和穷举的代码独立编码,但未保留代码的开始时间时,通常不清楚如何对协议对进行对齐。然而,在可以计算共同协议统计量Cohen的kappa之前,需要进行这种对齐。在这里,我们描述了一种基于最初设计用于比对核苷酸序列的Needleman and Wunsch(1970)算法的方法,用于最佳地比对此类序列。我们还提供了对对准kappa行为进行仿真研究的结果,该行为具有多个变量,包括代码数量,观察者准确性的不同程度,序列长度,代码可变性以及控制对准算法的参数。我们得出的结论是:(1)在最合理的情况下,观察者的准确性达到90%或更高会导致对齐kappas达到0.60或更高; (2)一般而言,比对kappas不受序列长度,编码数量或编码概率变化的强烈影响; (3)当可能错过事件和错误警报时,对齐卡伯会受到不利影响; (4)算法中使用的成本矩阵和优先级顺序应优先于替换(即意见分歧)而不是插入和删除(即事件遗漏和误报)。开发了两个计算机程序:用于进行模拟研究的全局序列比对(GSA)和事件比对或ELign,这是一个用户导向程序,用于计算比对k并在给定一对事件序列的情况下提供最佳比对。

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