Causal Inferences for treatment moderators on Zero-Inflated outcomes of HIV risk

治疗调节者对艾滋病毒风险零膨胀结果的因果推论

• 批准号: 9118944
• 负责人: Robert Gallop
• 金额: $ 14.73万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-15 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9118944
• 关键词: Address; Adopted; Age; Alcohol or Other Drugs use; Binomial Model; Clinical; Clinical Trials Network; Cocaine; Collaborations; Computer software; Data; Data Set; Databases; Development; Diagnostic; Diagnostic Procedure; Drug usage; Educational Intervention; Effect Modifiers (Epidemiology); Effectiveness; Gender; Goals; Greenland; HIV; HIV risk; HIV/STD; Health; Individual; Intervention; Investigation; Knowledge; Male Condoms; Methods; Modeling; National Institute of Drug Abuse; Negative Binomial Distributions; Outcome; Outcome Measure; Outcome Study; Outpatients; Pharmaceutical Preparations; Population; Procedures; Psychotherapy; Randomized; Randomized Clinical Trials; Research; Research Personnel; Robin bird; Safe Sex; Severities; Statistical Methods; Statistical Models; Structure; Substance abuse problem; Target Populations; Testing; Treatment Effectiveness; Universities; base; causal model; clinically relevant; follow-up; interest; men; mental state; methadone maintenance; primary outcome; response; simulation; skills; software development; treatment as usual; treatment program; web site

DESCRIPTION (provided by applicant): This proposal addresses two statistical issues in substance abuse research (1) the development of causal inference model for count response variable with a high preponderance of zeros (i.e. zero-inflated outcomes), and (2) accommodation of treatment moderators to the causal inference modeling paradigm for zero-inflated outcomes. Our recent collaborations with the University of Rochester has exposed us to data consisting of zero-inflated outcomes as examined within two NIDA Clinical Trials Network (CTN) studies: CTN0018 ("HIV/STD Safer Sex Skills Groups For Men In Methadone Maintenance Or Drug-free Outpatient Treatment Programs") and CTN0019 ("HIV/STD Safer Sex Skills Groups For Men In Methadone Maintenance Or Drug-free Outpatient Treatment Programs"). These studies examined the effectiveness of a five session gender-specific HIV sexual skill intervention relative to a one session "treatment as usual" standard HIV education intervention. Our previous research focused on standard modeling methods for assessment of moderation within a combined CTN0018 and CTN0019 database. Our colleagues at Rochester are focused on development of distribution-free models to assess moderation for zero-inflated outcomes in the combined database. These standard and distribution-free methods, however, do not address potential confounding between the moderator and other unmeasured variables. This in turn, has led to our interest in extending the causal inference modeling structure to accommodate moderation investigations with zero-inflated outcomes. Our general goals in this proposal are to (1) develop a causal inference statistical model for analysis of zero-inflated count data using Rubin's counterfactual framework under a specific Structural mean models (SMM; Robins, 1994; Robins, 2003) called the rank preserving model (RPM; Ten Have et al., 2007), (2) implement methods of the analysis of moderation under this causal inference framework, and (3) create software for implementing these new causal inference methods for zero-inflated outcomes. Within the context of the CTN0018/19 pooled database, we will test the new models by examining several clinically relevant moderators that were evident using standard moderation analyses: drug use severity, poly-drug use, whether or not the primary drug abused was cocaine, age, knowledge and understanding of male condom usage, and mini-mental status score. The new statistical methods and associated software will be disseminated so that other investigators can test for causal effects of moderator variables when study outcomes are zero-inflated.

描述（由申请人提供）：该提案解决了药物滥用研究中的两个统计问题（1）计数响应变量的因果推理模型的发展，具有零零的优势（即零膨胀结果），以及（2）将治疗调节剂适用于治疗调节剂，以使治疗调节剂对零额外介绍的因果关系模拟态度的因果关系模型。我们最近与罗切斯特大学的合作使我们接触了由零膨胀结果组成的数据，这些结果在两个NIDA临床试验网络（CTN）研究中所检查的研究：CTN0018（“ HIV/STD/STD更安全的性别技能小组，用于男性在美沙酮维护或无药物治疗方案或ctn0019（ctn0019）中的无毒品/SA SA SA SASD SASED（“ HIV）（“ HIV））（”门诊治疗计划”）。这些研究研究了相对于一场“像往常”的标准艾滋病毒教育干预措施的一次“治疗”，五次特定于性别的艾滋病毒性技能干预的有效性。我们以前的研究重点是评估组合CTN0018和CTN0019数据库中适度的标准建模方法。我们在罗切斯特的同事着重于开发无分配模型，以评估合并数据库中零膨胀结果的适度。但是，这些标准和无分配方法并不能解决主持人与其他未衡量变量之间的潜在混淆。反过来，这导致了我们对扩展因果推理建模结构的兴趣，以适应以零泄漏结果的适度调查。 Our general goals in this proposal are to (1) develop a causal inference statistical model for analysis of zero-inflated count data using Rubin's counterfactual framework under a specific Structural mean models (SMM; Robins, 1994; Robins, 2003) called the rank preserving model (RPM; Ten Have et al., 2007), (2) implement methods of the analysis of moderation under this causal inference framework, and (3) create software for implementing这些新的因果推理方法用于零膨胀结果。在CTN0018/19汇总数据库的背景下，我们将通过检查几个使用标准调节分析的临床相关的调节器来测试新模型：药物使用严重性，多毒用药物的使用，无论是否滥用主要药物，无论是可卡因，年龄，年龄，知识和对男性供应的年龄，知识和了解男性供应，以及男性供应和小型娱乐状况。新的统计方法和相关的软件将被传播，以便其他研究人员可以在研究结果偏移零时测试主持人变量的因果效应。