AN APPLICATION OF PRINCIPAL STRATIFICATION TO CONTROL FOR INSTITUTIONALIZATION AT FOLLOW-UP IN STUDIES OF SUBSTANCE ABUSE TREATMENT PROGRAMS
AN APPLICATION OF PRINCIPAL STRATIFICATION TO CONTROL FOR INSTITUTIONALIZATION AT FOLLOW-UP IN STUDIES OF SUBSTANCE ABUSE TREATMENT PROGRAMS
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DOI：
10.1214/08-aoas179
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发表时间：
2008-09-01
影响因子：
1.8
通讯作者：
Morral, Andrew R.
中科院分区：
文献类型：
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作者：
Griffin, Beth Ann;McCaffrey, Daniel F.;Morral, Andrew R.
关于戒毒治疗和刑事司法系统干预措施影响的纵向研究的参与者面临被送入收容所的高风险（例如，在他们吸毒、犯罪或从事危险行为的自由可能受到限制的环境中度过一段时间）。用于估计治疗效果的方法，在随访期间存在的机构可能是高度敏感的假设，不太可能在应用程序中得到满足，因此可能产生误导性的推论。本文考虑在随访时运用主体分层法对机构化进行控制。对于由于脱落、死亡或其他形式的删失而无法观察到研究参与者样本结果的类似问题，建议进行主要分层。该方法确定的主要状态，其中因果关系的影响是明确的，并可能估计。我们扩展的主要分层的方法，在后续的制度化和估计的影响，住宅药物滥用治疗与门诊服务的青少年药物滥用治疗计划的大规模研究。此外，我们还讨论了将主分层模型应用于数据的实际问题。我们通过模拟研究表明，该模型只能恢复真实的影响，提供的数据满足艰苦的要求，必须谨慎执行时，主要分层作为一种技术，以控制治疗后的混杂因素，如制度化。
Participants in longitudinal studies on the effects of drug treatment and criminal justice system interventions are at high risk for institutionalization (e.g., spending time in an environment where their freedom to use drugs, commit crimes, or engage in risky behavior may be circumscribed). Methods used for estimating treatment effects in the presence of institutionalization during follow-up can be highly sensitive to assumptions that are unlikely to be met in applications and thus likely to yield misleading inferences. In this paper were consider the use of principal stratification to control for institutionalization at follow-up. Principal stratification has been suggested for similar problems where outcomes are unobservable for samples of study participants because of dropout, death or other forms of censoring. The method identifies principal state within which causal effects are well defined and potentially estimable. We extend the method of principal stratification to model institutionalization at follow-up and estimate the effect of residential substance abuse treatment versus outpatient services in a large scale study of adolescent substance abuse treatment programs. Additionally, we discuss practical issues in applying the principal stratification model to data. We show via simulation studies that the model can only recover true effects provided the data meet strenuous demands and that there must be caution taken when implementing principal stratification as a technique to control for post-treatment confounders such as institutionalization.