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A case study in comparing therapies involving informative drop-out, non-ignorable non-compliance and repeated measurements.

机译:一个案例研究,用于比较涉及信息量下降,不可忽视的不依从和重复测量的疗法。

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Virtually no comparisons of different psychotherapies with long follow-up times have been carried out until now. The Helsinki Psychotherapy Study is a randomized clinical trial, where patients were monitored for 12 months after the onset of study treatments, of which each lasted approximately 6 months. The patients' psychiatric status was measured at five pre-determined time points during the follow-up period. In general, the analyses of trials are complicated in cases where compliance with the given treatment is incomplete or the drop-out from the follow-up is non-ignorable. In the present study, the quality of the treatment deviated from the protocol for some patients and some patients took auxiliary treatments which had similar effects to the study treatment during the study treatment or follow-up period. This might have resulted in standard intention-to-treat analyses providing excessively conservative or liberal conclusions. Non-compliance may have been non-ignorable in some cases, so subject-specific latent factors may have influenced the outcome both directly and indirectly via compliance behaviour. The most and least healthy patients are the most likely to dropout from the follow-up a priori, so the missing data process is informative. The missing data can partly be augmented with surrogate information collected during interviews with patients who dropped out. A Bayesian hierarchical as-treated model, which uses random-effects-based selection models to account for non-ignorable missing data and non-compliance, was compared with different mixed effects models.
机译:到目前为止,几乎没有对随访时间长的不同心理疗法进行比较。赫尔辛基心理疗法研究是一项随机临床试验,在开始研究治疗后,对患者进行了12个月的监测,每个治疗持续约6个月。在随访期间的五个预定时间点测量患者的精神状态。通常,如果对给定治疗的依从性不完全或无法从随访中撤出,则对试验的分析很复杂。在本研究中,某些患者的治疗质量与方案有所出入,一些患者在研究治疗或随访期间采取了与研究治疗相似的辅助治疗。这可能导致标准的意向性治疗分析提供了过于保守或宽松的结论。在某些情况下,不合规可能是不可忽视的,因此特定对象的潜在因素可能通过合规行为直接或间接影响了结果。最健康和最不健康的患者最有可能先验后辍学,因此缺失的数据过程是有益的。缺失的数据可以部分与在接受辍学患者的访谈中收集的替代信息相结合。将贝叶斯分层处理模型与不同的混合效应模型进行比较,该模型使用基于随机效应的选择模型来说明不可忽略的缺失数据和违规情况。

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