Power Analysis for Cluster Randomized Trials

整群随机试验的功效分析

基本信息

批准号：
7537513
负责人：
Michael Borenstein
金额：
$ 16.82万
依托单位：
BIOSTATISTICAL PROGRAMMING ASSOC, INC.
依托单位国家：
美国
项目类别：
财政年份：
2008
资助国家：
美国
起止时间：
2008-06-01 至 2008-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7537513
关键词：
20 year old Accounting Address Advertising Affect Alcohol abuse Alcohol consumption Am 80 Ambulances American Analysis of Variance Appendix Area Caring Clinic Clinics and Hospitals Cluster Analysis Communities Complex Computer software Condition Data Data Analyses Data Collection Databases Dimensions Drops Drug usage Elderly Enrollment Equilibrium Event Fall prevention Frequencies Funding Agency Gerontology Goals Gold Graph Health Heart Home environment Hospitals Illicit Drugs Individual Intervention Journals Lead Life Literature Medical Medicine Minnesota Modeling Negative Finding Numbers Output Palliative Care Patients Personal Satisfaction Persons Play Policy Research Poliomyelitis Prevention Preventive Medicine Primary Health Care Procedures Process Provider PubMed Public Health Publishing Randomized Randomized Controlled Clinical Trials Range Recruitment Activity Reporting Research Research Design Research Personnel Resources Risk Role SAS Sample Size Sampling Schools Series Services Side Social Policies Social Sciences Standards of Weights and Measures Statistically Significant Stroke Structure Students Substance abuse problem Sum Surveys Survival Analysis Tail Techniques Testing Time Vaccines Work Workplace cooking cost design editorial grasp improved functioning mortality motivational enhancement therapy programs simulation size smoking cessation software development treatment effect trend wasting

项目摘要

DESCRIPTION (provided by applicant): Cluster randomized trials are trials in which intact units such as hospitals, clinics, or schools, are randomly assigned to a condition such as Treatment or Control. Cluster randomized trials play a prominent role in medicine, health, and social policy research, accounting for some 11,000 trials in these areas, and the use of these trials has been accelerating in recent years. The statistical procedures required to plan and to analyze a cluster randomized trial are substantially more complex than those used for simple randomized trials. Popular software packages such as SPSS, SAS, and Stata include modules for the analysis of cluster randomized trials, and some 80% of these trials are analyzed using these kinds of modules. By contrast, no commercial software exists to compute power for these trials. Therefore, only about 20% of these trials use the proper techniques to compute power when these studies are being planned. This is a serious problem, since power for the cluster randomized design typically drops by at least 50%, and often by more, as compared with a simple randomized design with the same total sample size. The goal of this project is to develop software to compute power for cluster randomized trials. The program will work with studies that include two, three or four levels in the hierarchy. It will incorporate a sophisticated user interface to address the kinds of real-world issues that must be addressed in a power analysis. On the input side, it will allow users to enter the kinds of data that they are likely to have, and to do so using a clear and intuitive interface. On the output side the program will create tables and graphs that allow the user to quickly assess the impact of all assumptions, and to determine how changes in the design would affect power and costs. PUBLIC HEALTH RELEVANCE Cluster randomized trials are trials in which intact units such as hospitals, clinics, or schools, are randomly assigned to a condition such as Treatment or Control. These kinds of trials play a prominent role in medicine, health, and social policy research, with as many as 1,000 such trials being planned each year. The goal of this project is to develop software to perform a power analysis for cluster randomized trials, and enable researchers to design these trials in a manner that yields maximum power for the smallest cost.

说明（由申请人提供）：整群随机试验是指将医院、诊所或学校等完整单位随机分配给治疗或对照等条件的试验。整群随机试验在医学、卫生和社会政策研究中发挥着重要作用，这些领域约有 11,000 项试验，而且近年来这些试验的使用一直在加速。计划和分析整群随机试验所需的统计程序比简单随机试验所使用的统计程序要复杂得多。 SPSS、SAS 和 Stata 等流行软件包包含用于分析整群随机试验的模块，其中约 80% 的试验是使用此类模块进行分析的。相比之下，没有商业软件可以计算这些试验的能力。因此，在计划这些研究时，只有大约 20% 的试验使用适当的技术来计算功效。这是一个严重的问题，因为与总样本量相同的简单随机设计相比，整群随机设计的功效通常下降至少 50%，而且往往下降更多。该项目的目标是开发软件来计算集群随机试验的能力。该计划将适用于层次结构中包含两个、三个或四个级别的研究。它将采用复杂的用户界面来解决功率分析中必须解决的各种现实问题。在输入方面，它将允许用户输入他们可能拥有的数据类型，并使用清晰直观的界面来完成此操作。在输出方面，程序将创建表格和图表，使用户能够快速评估所有假设的影响，并确定设计中的更改将如何影响功耗和成本。公共卫生相关性整群随机试验是指将完整的单位（例如医院、诊所或学校）随机分配给治疗或对照等条件的试验。此类试验在医学、健康和社会政策研究中发挥着重要作用，每年计划进行多达 1,000 项此类试验。该项目的目标是开发软件来对集群随机试验进行功效分析，并使研究人员能够以最小的成本产生最大功效的方式设计这些试验。