Power Analysis for Cluster Randomized Trials
Power Analysis for Cluster Randomized Trials
批准号:
7626977
负责人:
Michael Borenstein
金额:
$42.53万
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-06-01 至 2010-12-31
关键词:
20 year oldAccountingAddressAdvertisingAffectAlcohol abuseAlcohol consumptionAm 80AmbulancesAmericanAnalysis of VarianceAreaCaringClinicClinical Trials DesignClinics and HospitalsCluster AnalysisCommunitiesComplexComputer softwareDataData AnalysesData CollectionDatabasesDropsDrug usageElderlyEnrollmentEventFall preventionFrequenciesFunding AgencyGerontologyGoalsGoldGraphHealthHeartHome environmentHospitalsIllicit DrugsIndividualInterventionJournalsLeadLifeLiteratureMedicalMedicineMinnesotaModelingNegative FindingOutputPalliative CarePatientsPersonsPlayPolicy ResearchPoliomyelitisPreventive MedicinePrimary Health CareProceduresProcessProviderPubMedPublic HealthPublishingRandomizedRandomized Controlled Clinical TrialsRecruitment ActivityReportingResearchResearch DesignResearch PersonnelResourcesRiskRoleSample SizeSamplingSchoolsSeriesServicesSideSocial PoliciesSocial SciencesStrokeStudentsSumSurveysSurvival AnalysisTailTechniquesTestingTimeVaccinesWorkWorkplaceabstractingcookingcostdesigneditorialimproved functioningmortalitymotivational enhancement therapyprogramssimulationsmoking cessationsoftware developmentsubstance abuse preventiontreatment effecttrendwasting
中文摘要
描述(由申请人提供):群集性随机试验是指将医院、诊所或学校等完好的单位随机分配到治疗或对照等条件下的试验。组群随机试验在医学、卫生和社会政策研究中发挥着突出的作用,在这些领域中约有1.1万项试验,近年来这些试验的使用速度不断加快。计划和分析整群随机试验所需的统计程序比用于简单随机试验的统计程序要复杂得多。诸如SPSS、SAS和STATA等流行的软件包包括用于分析整群随机试验的模块,并且大约80%的这些试验使用这些类型的模块进行分析。相比之下,目前还没有商业软件来计算这些试验的功率。因此,在这些试验中,只有大约20%在计划这些研究时使用适当的技术来计算功率。这是一个严重的问题,因为与具有相同总样本量的简单随机设计相比,集群随机设计的功率通常下降至少50%,并且往往下降更多。这个项目的目标是开发软件来计算集群随机试验的功率。该计划将与包括两个、三个或四个层次的研究一起工作。它将包含一个复杂的用户界面,以解决电力分析中必须解决的各种现实问题。在输入端,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进行输入。在输出端,该程序将创建表格和图表,允许用户快速评估所有假设的影响,并确定设计中的变化将如何影响电力和成本。公共卫生相关性群组随机试验是指将医院、诊所或学校等完好的单位随机分配到治疗或对照等条件下进行的试验。这类试验在医学、卫生和社会政策研究中发挥着重要作用,每年计划进行的此类试验多达1000项。这个项目的目标是开发软件来执行集群随机试验的功率分析,并使研究人员能够以最小的成本产生最大的功率来设计这些试验。
英文摘要
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.
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