Mariola Moeyaert, Panpan Yang, Xinyun Xu, Esther Kim
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Prior to extending methodological work validating the hierarchical linear model including moderators at the different levels, an overview of characteristics of moderators typically encountered in the field is needed. This will inform design conditions to be embedded in future methodological studies and ensure that these conditions are realistic and representative for the field of SCED meta-analyses. This study presents the results of systematic review of SCED meta-analyses, with the particular focus on moderator characteristic. The initial search yielded a total of 910 articles and book chapters. After excluding duplicate studies and non peer-reviewed studies, 658 unique peer-reviewed studies were maintained and screened by two independent researchers. Sixty articles met the inclusion criteria and were eligible for data retrieval. The results of the analysis of moderator characteristics retrieved from these 60 meta-analyses are presented. The first part of the results section contains an overview of moderator characteristics per moderator level (within-participant level, participant level, and study level), including the types of moderators, the ratio of the number of moderators relative to the number of units at that level, the measurement scale, and the degree of missing data. The second part of the results section focuses on the metric used to quantify moderator effectiveness and the analysis approach. Based on the results of the systematic review, recommendations are given for conditions to be included in future methodological work.</p>","PeriodicalId":48037,"journal":{"name":"Behavior Modification","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/01454455211002111","citationCount":"6","resultStr":"{\"title\":\"Characteristics of Moderators in Meta-Analyses of Single-Case Experimental Design Studies.\",\"authors\":\"Mariola Moeyaert, Panpan Yang, Xinyun Xu, Esther Kim\",\"doi\":\"10.1177/01454455211002111\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Hierarchical linear modeling (HLM) has been recommended as a meta-analytic technique for the quantitative synthesis of single-case experimental design (SCED) studies. 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The initial search yielded a total of 910 articles and book chapters. After excluding duplicate studies and non peer-reviewed studies, 658 unique peer-reviewed studies were maintained and screened by two independent researchers. Sixty articles met the inclusion criteria and were eligible for data retrieval. The results of the analysis of moderator characteristics retrieved from these 60 meta-analyses are presented. The first part of the results section contains an overview of moderator characteristics per moderator level (within-participant level, participant level, and study level), including the types of moderators, the ratio of the number of moderators relative to the number of units at that level, the measurement scale, and the degree of missing data. The second part of the results section focuses on the metric used to quantify moderator effectiveness and the analysis approach. 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Characteristics of Moderators in Meta-Analyses of Single-Case Experimental Design Studies.
Hierarchical linear modeling (HLM) has been recommended as a meta-analytic technique for the quantitative synthesis of single-case experimental design (SCED) studies. The HLM approach is flexible and can model a variety of different SCED data complexities, such as intervention heterogeneity. A major advantage of using HLM is that participant and-or study characteristics can be incorporated in the model in an attempt to explain intervention heterogeneity. The inclusion of moderators in the context of meta-analysis of SCED studies did not yet receive attention and is in need of methodological research. Prior to extending methodological work validating the hierarchical linear model including moderators at the different levels, an overview of characteristics of moderators typically encountered in the field is needed. This will inform design conditions to be embedded in future methodological studies and ensure that these conditions are realistic and representative for the field of SCED meta-analyses. This study presents the results of systematic review of SCED meta-analyses, with the particular focus on moderator characteristic. The initial search yielded a total of 910 articles and book chapters. After excluding duplicate studies and non peer-reviewed studies, 658 unique peer-reviewed studies were maintained and screened by two independent researchers. Sixty articles met the inclusion criteria and were eligible for data retrieval. The results of the analysis of moderator characteristics retrieved from these 60 meta-analyses are presented. The first part of the results section contains an overview of moderator characteristics per moderator level (within-participant level, participant level, and study level), including the types of moderators, the ratio of the number of moderators relative to the number of units at that level, the measurement scale, and the degree of missing data. The second part of the results section focuses on the metric used to quantify moderator effectiveness and the analysis approach. Based on the results of the systematic review, recommendations are given for conditions to be included in future methodological work.
期刊介绍:
For two decades, researchers and practitioners have turned to Behavior Modification for current scholarship on applied behavior modification. Starting in 1995, in addition to keeping you informed on assessment and modification techniques relevant to psychiatric, clinical, education, and rehabilitation settings, Behavior Modification revised and expanded its focus to include treatment manuals and program descriptions. With these features you can follow the process of clinical research and see how it can be applied to your own work. And, with Behavior Modification, successful clinical and administrative experts have an outlet for sharing their solutions in the field.