Toward a Generalized Framework and Flexible Software Environment for Power Analysis of Alcohol Treatment Randomized Controlled Trials

为酒精治疗随机对照试验的功效分析建立通用框架和灵活的软件环境

基本信息

  • 批准号:
    10240574
  • 负责人:
  • 金额:
    $ 67.17万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-09-20 至 2023-08-31
  • 项目状态:
    已结题

项目摘要

PROJECT SUMMARY Pharmacological and behavioral treatments of alcohol use disorder are only useful to the extent that their effects are robust and reliable. A priori determination of statistical power is one of the most significant steps to maximizing scientific reliability; however, it has historically been largely overlooked in the health sciences. Alcohol researchers are increasingly utilizing complex statistical models (e.g., growth curves, mixture models, social networks); yet, accessible methods for sample size determination for all but the simplest statistical tests have not been broadly disseminated. Moreover, even for models in which software programs are readily available, scientists consistently express uncertainty regarding expected parameter estimates, prohibiting the utility of power analysis itself. As a result, many randomized controlled trials (RCTs) are likely not optimally designed to allow for conclusive statistical inference. The overall objective of this proposal is to close this gap by developing a generalized method for power analysis using a combination of established and innovative approaches that can be used to generate and test a vast array of models used in treatment research. This objective will be achieved by pursuing two specific aims: develop a flexible, user-friendly software interface for statistical power and sensitivity analysis (Aim 1); and develop a generalized framework for determining model parameter estimates (Aim 2). The proposal is innovative because the software interface will be grounded in state-of-the-art advancements in computational technology and human-computer interaction. In addition, the framework will be fortified by advances in generalizability-theory-based meta-analyses and guided walk and machine-learning-based simulation studies investigating the effects of uncertainty in individual model parameters on the likelihood of observing hypothesized effects. The software will include automated sensitivity analyses to identify parameters with the largest impact on power and will recommend starting parameters. Development and testing will be grounded in the naltrexone and cognitive behavioral therapy literatures. Their widespread use and diversity of methodological approaches make them ideal testbeds from which to generalize to other treatment domains. This research is synergistic with each of the goals within the NIAAA Strategic Plan (2017-2021). Perhaps most significantly, methodology and guidelines will be developed for designing RCTs that have sufficient precision to distinguish trajectories, mechanisms, heterogeneity, and specificity of treatment efficacy. These efforts will provide researchers with the required a priori information to execute studies that ensure the robustness of their results. The development of these tools for RCT design will have implications for all areas of alcohol treatment research, including in-the-moment risk behaviors, person- level (comorbid) characteristics, targeting underserved and vulnerable populations, and large-scale initiatives. As a result, this proposal will allow for more definitive identification of efficacious interventions and treatments of alcohol use disorder.
项目摘要 酒精使用障碍的药理学和行为治疗仅在其有效程度上是有用的。 效果稳健可靠。统计功效的先验确定是最重要的步骤之一 最大限度地提高科学的可靠性;然而,它在历史上在很大程度上被忽视的健康科学。 酒精研究人员越来越多地利用复杂的统计模型(例如,增长曲线,混合模型, 社交网络);然而,除了最简单的统计测试之外, 没有得到广泛传播。此外,即使对于其中软件程序易于 可用,科学家一致表示对预期参数估计的不确定性, 电力分析本身。因此,许多随机对照试验(RCT)可能不是最佳的 设计成允许结论性的统计推断。本提案的总体目标是缩小这一差距 通过开发一种通用的方法,使用现有的和创新的组合进行功率分析, 这些方法可用于生成和测试治疗研究中使用的大量模型。这 将通过以下两个具体目标实现这一目标:开发一个灵活、方便用户的软件界面, 统计功效和敏感性分析(目标1);以及制定一个确定模型的通用框架 参数估计(目标2)。该提案是创新的,因为软件界面将基于 计算技术和人机交互的最新进展。此外该 框架将通过基于概化理论的荟萃分析和引导性步行的进展得到加强, 基于机器学习的模拟研究,调查个体模型中不确定性的影响 观察假设效应的可能性的参数。该软件将包括自动灵敏度 分析以确定对功率影响最大的参数,并推荐启动参数。 开发和测试将以纳洛酮和认知行为疗法文献为基础。他们的 方法的广泛使用和多样性使它们成为理想的试验平台, 推广到其他治疗领域。这项研究与NIAAA中的每个目标都是协同的 战略计划(2017-2021年)。也许最重要的是,将制定方法和准则, 设计具有足够精确度的RCT,以区分轨迹、机制、异质性和 治疗效果的特异性。这些努力将为研究人员提供所需的先验信息, 执行研究,确保其结果的稳健性。这些RCT设计工具的开发将 对酒精治疗研究的所有领域都有影响,包括当下的危险行为,人, 针对得不到充分服务的弱势群体和大规模举措。 因此,该提案将允许更明确地确定有效的干预措施和治疗方法 酒精使用障碍

项目成果

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Erin Hennes其他文献

Erin Hennes的其他文献

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{{ truncateString('Erin Hennes', 18)}}的其他基金

Toward a Generalized Framework and Flexible Software Environment for Power Analysis of Alcohol Treatment Randomized Controlled Trials
为酒精治疗随机对照试验的功效分析建立通用框架和灵活的软件环境
  • 批准号:
    10733319
  • 财政年份:
    2018
  • 资助金额:
    $ 67.17万
  • 项目类别:

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