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How much can we learn about missing data?: an exploration of a clinical trial in psychiatry

机译:我们可以从丢失的数据中学到多少?:对精神病学临床试验的探索

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When a randomized controlled trial has missing outcome data, any analysis is based on untestable assumptions, e.g. that the data are missing at random, or less commonly on other assumptions about the missing data mechanism. Given such assumptions, there is an extensive literature on suitable methods of analysis. However, little is known about what assumptions are appropriate. We use two sources of ancillary data to explore the missing data mechanism in a trial of adherence therapy in patients with schizophrenia: carer-reported (proxy) outcomes and the number of contact attempts. This requires additional assumptions to be made whose plausibility we discuss. Proxy outcomes are found to be unhelpful in this trial because they are insufficiently associated with patient outcome and because the ancillary assumptions are implausible. The number of attempts required to achieve a follow-up interview is helpful and suggests that these data are unlikely to depart far from being missing at random. We also perform sensitivity analyses to departures from missingness at random, based on the investigators' prior beliefs elicited at the start of the trial. Wider use of techniques such as these will help to inform the choice of suitable assumptions for the analysis of randomized controlled trials.
机译:当随机对照试验缺少结果数据时,任何分析都基于无法检验的假设,例如数据是随机丢失的,或者在其他有关丢失数据机制的假设下很少丢失。给定这样的假设,有大量关于合适的分析方法的文献。但是,对于哪种假设是适当的知之甚少。在患有精神分裂症的患者进行依从性治疗的试验中,我们使用两种辅助数据来源来探索缺失的数据机制:护理者报告的(代理)结果和接触尝试的次数。这就需要做出其他假设,我们将讨论其合理性。在该试验中发现代理结局无济于事,因为它们与患者结局关联不充分,并且辅助假设令人难以置信。进行后续访谈所需的尝试次数是有帮助的,并表明这些数据不太可能远离随机丢失。我们还根据研究人员在试验开始时所得出的先前信念,随机进行了对缺失现象的敏感性分析。诸如此类技术的广泛使用将有助于为随机对照试验的分析选择合适的假设。

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