Integrative data analysis in clinical psychology research.

Integrative data analysis in clinical psychology research.
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DOI:
10.1146/annurev-clinpsy-050212-185522
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发表时间:
2013
影响因子:
18.4
通讯作者:
Bauer DJ
Bauer DJ
中科院分区:
心理学1区
文献类型:
--
作者:
Hussong AM;Curran PJ;Bauer DJ

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综合数据分析(IDA)是一种对来自多个研究的原始数据进行同时分析的新框架,它提供了许多优势,包括经济性(即现有数据的重复使用)、强大(即大的组合样本量)、解决单一贡献研究无法回答的新问题的潜力(例如,合并纵向研究以涵盖更广泛的生命周期)以及建立更累积的科学的机会(即,检查不同研究的影响的相似性和不同的潜在原因)。国际开发协会还面临方法学上的挑战,包括需要考虑不同研究之间的抽样异质性,制定不同研究之间的相称衡量标准,以及在影响假设检验时解释研究差异的多个来源。在这篇综述中,我们概述了这些挑战的潜在解决方案,并描述了发展IDA作为临床心理学研究框架的未来途径。
Integrative Data Analysis (IDA), a novel framework for conducting the simultaneous analysis of raw data pooled from multiple studies, offers many advantages including economy (i.e., reuse of extant data), power (i.e., large combined sample sizes), the potential to address new questions not answerable by a single contributing study (e.g., combining longitudinal studies to cover a broader swath of the lifespan), and the opportunity to build a more cumulative science (i.e., examining the similarity of effects across studies and potential reasons for dissimilarities). There are also methodological challenges associated with IDA, including the need to account for sampling heterogeneity across studies, to develop commensurate measures across studies, and to account for multiple sources of study differences as they impact hypothesis testing. In this review, we outline potential solutions to these challenges and describe future avenues for developing IDA as a framework for studies in clinical psychology.
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