Generalizing over encounters: Statistical and theoretical considerations

Author:

Barr Dale J.

Abstract

How do we evaluate evidence for the generality of phenomena in psycholinguistics and related fields? For decades, researchers have recognized the importance of treating not only participants, but also stimuli, as sampled rather than fixed (Clark, 1973). It is only by taking both subject and stimulus populations into account during analysis—and critically, doing so simultaneously—that claims about psycholinguistic phenomena are supported in their full generality. In this chapter, I argue that simultaneous by-subject and by-item analyses is a special (albeit common) case of a more general problem of generalizing over particular types of encounters, defined in terms of the sampled units involved in the situation and the connections between them. This approach is more general inasmuch as it encompasses the traditional two-party encounters between subjects and stimulus materials but also handles two-party dyadic communicative encounters, or even three-party encounters involving participants making judgments about stimuli that were produced by participants in response to other stimuli. I argue that the goal of analysis is to make claims that are maximally likely to generalize to new encounters of the same type, and propose that the relevant encounter types involved in an experiment can be identified by thinking about the boundaries of what would constitute a legitimate ‘replication’ of that experiment. These ideas have important implications far beyond psycholinguistics; indeed, nearly all areas of psychology and neuroscience make claims that are intended to generalize to new encounters, although it is only psycholinguistics that consistently uses the statistical apparatus requiredto support such claims.

Publisher

Center for Open Science

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3