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不完善依从性新药临床试验中疗效评价的工具变量估计 被引量:2

Estimating Treatment Effects by Instrumental Variables under Non-Compliance in Randomized Clinical Trials
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摘要 随机对照临床试验中的意向治疗分析总是假设受试者具有完善的依从性,再来比较治疗组和对照组之间的疗效差异。然而,在临床试验中不依从是普遍存在的,受试者的依从性与试验结果的质量密切相关,不依从或依从性差是导致治疗无效的最常见的原因,在进行药物的疗效评价时,也是造成偏倚的一个重要的因素。本研究考虑在不完善依从性条件下,用工具变量给出药物疗效的评价方法。 In randomied clinical trials, the intention to treat approach has long served as a standard methodological procedure, which just compare response distributions by assignment, ignoring information on compliance. In fact, however, non-compliance is common in many trials. Moreover, compliance is related to the quality of treatment evaluation' Many erroneous conclusion is usually attributed to non--compliance, and non-compliance can also lead to a bias on treatment effects evaluating. This paper presents an estimator of treatment effects by instrumental variables under non-compliance.
出处 《数理医药学杂志》 2008年第5期572-573,共2页 Journal of Mathematical Medicine
关键词 疗效评价 随机临床试验 非依从性 工具变量 estimating treatment effects randomized clinical trials non-compliance instrumental vari-able
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参考文献4

  • 1Bang Heejung, Davis Clarence E. On estimating treatment effects under non-compliance in randomized clinical trials: Are intent-to- treat or instrumental variables analyses perfect solutions. Statistics in Medicine, 2007,26 : 954-964.
  • 2Sun Junfeng , Nagaraja H N, Reynolds Nancy R. Discrete stochastic models for cCompliance analysis based on an AIDS Clinical Trial Group (ACTG) study. Biometrical Journal, 2007,49 : 731-741.
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同被引文献20

  • 1易丹辉,李芃芃,童小军.中医临床疗效评价的统计方法[J].世界科学技术-中医药现代化,2007,9(4):81-85. 被引量:6
  • 2Hernan M A, Robins J M. Instruments for causal inference: anepidemiologist's dream? Epidemiology, 2006, 17(4): 360-372.
  • 3Brookhart M A, Schneeweiss S, Rothman K J, et al. Variable selectionfor propensity score models. Am J Epidemiol, 2006,163(12): 1149-1156.
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  • 7Balke A, Pearl J. Bounds on treatment effects from studies withimperfect compliance. J Am Stat Assoc, 1997, 92(439): 1171-1176.
  • 8MacLehose R F, Kaufman S, Kaufman J S, et al. Bounding causal effectsunder uncontrolled confounding using counterfactuals. Epidemiology,2005, 16(4): 548-555.
  • 9Joshua D A,Guido W I, Donald B R. Identification of Causal EffectsUsing Instrumental Variables. J Am Stat Assoc, 1996,91(434): 444-455.
  • 10Ho V,Hamilton B H,Rools L L. Multiple approaches to assessingthe effects of delays for hip fracture patients in the United States andCanada. Health Serv Res, 2000, 34(7): 1499-1518.

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