Ottavia M Epifania, Pasquale Anselmi, Egidio Robusto
{"title":"线性混合效应模型指导教程,用于分析完全交叉设计实验中的精确度和响应时间。","authors":"Ottavia M Epifania, Pasquale Anselmi, Egidio Robusto","doi":"10.1037/met0000708","DOIUrl":null,"url":null,"abstract":"<p><p>Experiments with fully crossed designs are often used in experimental psychology spanning several fields, from cognitive psychology to social cognition. These experiments consist in the presentation of stimuli representing super-ordinate categories, which have to be sorted into the correct category in two contrasting conditions. This tutorial presents a linear mixed-effects model approach for obtaining Rasch-like parameterizations of response times and accuracies of fully crossed design data. The modeling framework for the analysis of fully crossed design data is outlined along with a step-by-step guide of its application, which is further illustrated with two practical examples based on empirical data. The first example regards a cognitive psychology experiment and pertains to the evaluation of a spatial-numerical association of response codes effect. The second one is based on a social cognition experiment for the implicit evaluation of racial attitudes. A fully commented R script for reproducing the analyses illustrated in the examples is available in the online supplemental materials. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":" ","pages":""},"PeriodicalIF":7.6000,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A guided tutorial on linear mixed-effects models for the analysis of accuracies and response times in experiments with fully crossed design.\",\"authors\":\"Ottavia M Epifania, Pasquale Anselmi, Egidio Robusto\",\"doi\":\"10.1037/met0000708\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Experiments with fully crossed designs are often used in experimental psychology spanning several fields, from cognitive psychology to social cognition. These experiments consist in the presentation of stimuli representing super-ordinate categories, which have to be sorted into the correct category in two contrasting conditions. This tutorial presents a linear mixed-effects model approach for obtaining Rasch-like parameterizations of response times and accuracies of fully crossed design data. The modeling framework for the analysis of fully crossed design data is outlined along with a step-by-step guide of its application, which is further illustrated with two practical examples based on empirical data. The first example regards a cognitive psychology experiment and pertains to the evaluation of a spatial-numerical association of response codes effect. The second one is based on a social cognition experiment for the implicit evaluation of racial attitudes. A fully commented R script for reproducing the analyses illustrated in the examples is available in the online supplemental materials. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>\",\"PeriodicalId\":20782,\"journal\":{\"name\":\"Psychological methods\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":7.6000,\"publicationDate\":\"2024-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Psychological methods\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1037/met0000708\",\"RegionNum\":1,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychological methods","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1037/met0000708","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
摘要
在认知心理学和社会认知等多个领域的实验心理学中,经常会用到完全交叉设计的实验。这些实验包括呈现代表上位类别的刺激物,这些刺激物必须在两种对比条件下被分类到正确的类别中。本教程介绍了一种线性混合效应模型方法,用于获取完全交叉设计数据的响应时间和准确率的 Rasch 类参数。本教程概述了用于分析完全交叉设计数据的建模框架,并提供了应用该框架的分步指南。第一个例子涉及认知心理学实验,与反应代码的空间-数字关联效应评估有关。第二个例子是基于种族态度内隐评估的社会认知实验。在线补充材料中提供了一个完整注释的 R 脚本,用于重现示例中的分析。(PsycInfo 数据库记录 (c) 2024 APA,保留所有权利)。
A guided tutorial on linear mixed-effects models for the analysis of accuracies and response times in experiments with fully crossed design.
Experiments with fully crossed designs are often used in experimental psychology spanning several fields, from cognitive psychology to social cognition. These experiments consist in the presentation of stimuli representing super-ordinate categories, which have to be sorted into the correct category in two contrasting conditions. This tutorial presents a linear mixed-effects model approach for obtaining Rasch-like parameterizations of response times and accuracies of fully crossed design data. The modeling framework for the analysis of fully crossed design data is outlined along with a step-by-step guide of its application, which is further illustrated with two practical examples based on empirical data. The first example regards a cognitive psychology experiment and pertains to the evaluation of a spatial-numerical association of response codes effect. The second one is based on a social cognition experiment for the implicit evaluation of racial attitudes. A fully commented R script for reproducing the analyses illustrated in the examples is available in the online supplemental materials. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
期刊介绍:
Psychological Methods is devoted to the development and dissemination of methods for collecting, analyzing, understanding, and interpreting psychological data. Its purpose is the dissemination of innovations in research design, measurement, methodology, and quantitative and qualitative analysis to the psychological community; its further purpose is to promote effective communication about related substantive and methodological issues. The audience is expected to be diverse and to include those who develop new procedures, those who are responsible for undergraduate and graduate training in design, measurement, and statistics, as well as those who employ those procedures in research.