Ginette Lafit, Jordan Revol, Leonie Cloos, Peter Kuppens, Eva Ceulemans
{"title":"不同的结构操作、研究持续时间和预处理选择对密集纵向研究中基于功率的样本量建议的影响。","authors":"Ginette Lafit, Jordan Revol, Leonie Cloos, Peter Kuppens, Eva Ceulemans","doi":"10.1177/10731911241286868","DOIUrl":null,"url":null,"abstract":"<p><p>To shed light on the dynamics of psychological processes, researchers often collect intensive longitudinal (IL) data by asking people to repeatedly report on their momentary experiences in daily life. Two important decisions when designing an IL study concern the number of persons and the number of measurement occasions to be included. These sample size decisions are ideally based on statistical power considerations. When conducting statistical power analysis, it is necessary to provide the value of the effect size of interest as well as of all other model parameters. In IL research, these values have to be based on previous studies. This implies that these values are subject to large heterogeneity due to differences in study design and preprocessing choices. This between-study heterogeneity can severely impact power-based sample size recommendations. In this article, we introduce an approach to investigate the impact of study design and pre-processing of previous studies and to determine a recommended sample size to account for this impact. We demonstrate how to use this approach to investigate the effect of different construct operationalizations, study duration, and preprocessing choices. This approach paves the way for more thoughtful and robust sample-size decisions.</p>","PeriodicalId":8577,"journal":{"name":"Assessment","volume":" ","pages":"10731911241286868"},"PeriodicalIF":3.5000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Effect of Different Construct Operationalizations, Study Duration, and Preprocessing Choices on Power-Based Sample Size Recommendations in Intensive Longitudinal Research.\",\"authors\":\"Ginette Lafit, Jordan Revol, Leonie Cloos, Peter Kuppens, Eva Ceulemans\",\"doi\":\"10.1177/10731911241286868\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>To shed light on the dynamics of psychological processes, researchers often collect intensive longitudinal (IL) data by asking people to repeatedly report on their momentary experiences in daily life. Two important decisions when designing an IL study concern the number of persons and the number of measurement occasions to be included. These sample size decisions are ideally based on statistical power considerations. When conducting statistical power analysis, it is necessary to provide the value of the effect size of interest as well as of all other model parameters. In IL research, these values have to be based on previous studies. This implies that these values are subject to large heterogeneity due to differences in study design and preprocessing choices. This between-study heterogeneity can severely impact power-based sample size recommendations. In this article, we introduce an approach to investigate the impact of study design and pre-processing of previous studies and to determine a recommended sample size to account for this impact. We demonstrate how to use this approach to investigate the effect of different construct operationalizations, study duration, and preprocessing choices. This approach paves the way for more thoughtful and robust sample-size decisions.</p>\",\"PeriodicalId\":8577,\"journal\":{\"name\":\"Assessment\",\"volume\":\" \",\"pages\":\"10731911241286868\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Assessment\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1177/10731911241286868\",\"RegionNum\":2,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, CLINICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Assessment","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1177/10731911241286868","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, CLINICAL","Score":null,"Total":0}
引用次数: 0
摘要
为了揭示心理过程的动态变化,研究人员经常通过要求人们反复报告日常生活中的瞬间经历来收集密集的纵向(IL)数据。在设计一项纵向研究时,有两个重要的决定涉及到研究对象的人数和测量场合的数量。这些样本数量的决定最好基于统计能力的考虑。在进行统计能力分析时,有必要提供相关效应大小以及所有其他模型参数的值。在 IL 研究中,这些值必须基于以往的研究。这意味着,由于研究设计和预处理选择的不同,这些值会有很大的异质性。这种研究间的异质性会严重影响基于功率的样本大小建议。在本文中,我们介绍了一种方法来调查研究设计和以往研究预处理的影响,并确定考虑到这种影响的推荐样本量。我们演示了如何使用这种方法来研究不同的构造操作、研究持续时间和预处理选择的影响。这种方法为更周到、更稳健的样本大小决策铺平了道路。
The Effect of Different Construct Operationalizations, Study Duration, and Preprocessing Choices on Power-Based Sample Size Recommendations in Intensive Longitudinal Research.
To shed light on the dynamics of psychological processes, researchers often collect intensive longitudinal (IL) data by asking people to repeatedly report on their momentary experiences in daily life. Two important decisions when designing an IL study concern the number of persons and the number of measurement occasions to be included. These sample size decisions are ideally based on statistical power considerations. When conducting statistical power analysis, it is necessary to provide the value of the effect size of interest as well as of all other model parameters. In IL research, these values have to be based on previous studies. This implies that these values are subject to large heterogeneity due to differences in study design and preprocessing choices. This between-study heterogeneity can severely impact power-based sample size recommendations. In this article, we introduce an approach to investigate the impact of study design and pre-processing of previous studies and to determine a recommended sample size to account for this impact. We demonstrate how to use this approach to investigate the effect of different construct operationalizations, study duration, and preprocessing choices. This approach paves the way for more thoughtful and robust sample-size decisions.
期刊介绍:
Assessment publishes articles in the domain of applied clinical assessment. The emphasis of this journal is on publication of information of relevance to the use of assessment measures, including test development, validation, and interpretation practices. The scope of the journal includes research that can inform assessment practices in mental health, forensic, medical, and other applied settings. Papers that focus on the assessment of cognitive and neuropsychological functioning, personality, and psychopathology are invited. Most papers published in Assessment report the results of original empirical research, however integrative review articles and scholarly case studies will also be considered.