Del Boca Frances K, Darkes Jack
Department of Psychology, University of South Florida, Tampa, FL 33620-8200, USA.
Addiction. 2007 Sep;102(9):1356-64. doi: 10.1111/j.1360-0443.2007.01864.x. Epub 2007 May 18.
This is the third paper in a series that reviews strategies for optimizing the validity and utility of randomized clinical trials (RCTs) in addictions treatment research. Whereas the two previous papers focused on design and implementation, here we address issues pertaining to data processing and statistical analysis.
Recommendations for enhancing data quality and utility are offered in sections on data coding and entry; and data format, structure and management. We discuss the need for preliminary data analyses that examine statistical power; patterns of attrition; between-group equivalence; and treatment integrity and discriminability. We discuss tests of treatment efficacy, as well as ancillary analyses aimed at explicating treatment processes.
Safeguards are necessary to protect data quality, and advance planning is needed to ensure that data formats are compatible with statistical objectives. In addition to treatment efficacy, statistical analyses should evaluate study internal and external validity, and investigate the change mechanisms that underlie treatment effects.
本文是系列文章中的第三篇，该系列文章回顾了优化成瘾治疗研究中随机临床试验（RCT）有效性和实用性的策略。前两篇文章聚焦于设计与实施，本文则探讨与数据处理和统计分析相关的问题。
在数据编码与录入以及数据格式、结构与管理部分，给出了提高数据质量和实用性的建议。我们讨论了进行初步数据分析的必要性，这些分析包括检验统计功效、损耗模式、组间等效性以及治疗完整性和可区分性。我们讨论了治疗效果的检验，以及旨在阐明治疗过程的辅助分析。
必须采取保障措施来保护数据质量，并且需要提前规划以确保数据格式与统计目标兼容。除了治疗效果之外，统计分析还应评估研究的内部和外部有效性，并探究治疗效果背后的变化机制。
