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Adaptive design in surveys and clinical trials: similarities, differences and opportunities for cross-fertilization

机译:调查和临床试验中的自适应设计:交叉施肥的相似之处,差异和机遇

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Adaptive designs involve preplanned rules for modifying an on-going study based on accruing data. We compare the goals and methods of adaptation for trials and surveys, identify similarities and differences, and make recommendations for what types of adaptive approaches from one domain have high potential to be useful in the other. For example, clinical trials could benefit from recently developed survey methods for monitoring which groups have low response rates and intervening to fix this. Clinical trials may also benefit from more formal identification of the target population, and from using paradata (contextual information collected before or during the collection of actual outcomes) to predict participant compliance and retention and then to intervene to improve these. Surveys could benefit from stopping rules based on information monitoring, applying techniques from sequential multiple-assignment randomized trial designs to improve response rates, prespecifying a formal adaptation protocol and including a data monitoring committee. We conclude with a discussion of the additional information, infrastructure and statistical analysis methods that are needed when conducting adaptive designs, as well as benefits and risks of adaptation.
机译:自适应设计涉及基于累计数据修改持续研究的预先预告规则。我们比较适应试验和调查的目标和方法,确定相似性和差异,并为来自一个领域的自适应方法的建议提出了高潜力的建议。例如,临床试验可以从最近开发的调查方法中受益,以监测哪些群体的响应率低,干预以解决这个问题。临床试验也可能受益于目标人口的更正式鉴定,并从使用帕拉多(在收集实际结果之前或期间收集的上下文信息)来预测参与者的遵守和保留,然后介入以改善这些。调查可以根据信息监控的停止规则,从顺序多分配随机试验设计的应用,以提高正式适应协议并包括数据监测委员会的响应率,包括数据监测委员会的响应率。我们结束了讨论进行自适应设计时所需的附加信息,基础设施和统计分析方法,以及适应的益处和风险。

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