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.

分层线性模型（HLM）已被推荐作为一种荟萃分析技术，用于单案例实验设计（SCED）研究的定量综合。HLM 方法非常灵活，可以对各种不同的 SCED 数据复杂性进行建模，例如干预异质性。使用 HLM 的一个主要优点是可以将参与者和/或研究特征纳入模型中，以尝试解释干预异质性。在 SCED 研究荟萃分析中纳入调节因素尚未受到关注，需要进行方法学研究。在扩展验证包括不同级别的调节器在内的分层线性模型的方法学工作之前，需要概述该领域中通常遇到的调节器的特征。这将为嵌入未来方法学研究的设计条件提供信息，并确保这些条件对于 SCED 荟萃分析领域来说是现实的和具有代表性的。本研究介绍了 SCED 荟萃分析的系统回顾结果，特别关注调节者特征。初步搜索共找到 910 篇文章和书籍章节。排除重复研究和非同行评审研究后，两名独立研究人员维护和筛选了 658 项独特的同行评审研究。六十篇文章符合纳入标准并有资格进行数据检索。展示了从这 60 项荟萃分析中检索到的调节者特征的分析结果。结果部分的第一部分包含每个主持人级别（参与者内部级别、参与者级别和研究级别）的主持人特征的概述，包括主持人的类型、主持人数量相对于单位数量的比率该水平、测量尺度以及缺失数据的程度。结果部分的第二部分重点介绍用于量化主持人有效性的指标和分析方法。根据系统评价的结果，对未来方法学工作中纳入的条件提出建议。