工具变量方法:中医药实效研究的统计分析利器

2016-06-16 陆芳、唐旭东等 MedSci原创

中医中药的治疗与现代医学有较大差别,不仅表现在药物上,也表现在处方的个性化,以及中医师本身的“经验”,而这些“经验”在统计学中称为意向性,其实都是临床研究中的偏倚(bias),经典的统计方法都无法处理这些很难测量的问题,这也是为什么中医治疗疾病的疗效往往呈现“千变万化”,不同的人结果可能完全不同的重要原因。 因此,需要寻找出有效规避这些不可测量的影响因素的统计学策略。实际上,在统计学中,这些

中医中药的治疗与现代医学有较大差别,不仅表现在药物上,也表现在处方的个性化,以及中医师本身的“经验”,而这些“经验”在统计学中称为意向性,其实都是临床研究中的偏倚(bias),经典的统计方法都无法处理这些很难测量的问题,这也是为什么中医治疗疾病的疗效往往呈现“千变万化”,不同的人结果可能完全不同的重要原因。 因此,需要寻找出有效规避这些不可测量的影响因素的统计学策略。实际上,在统计学中,这些不可测量的影响因素,实际上是“内生性变量”的一种重要形式。工具变量作为一种新型统计学策略,非常擅长处理内生性的问题。 实效研究是在实际医疗环境下,对具体中医药干预和实际操作最终结果的评估,并越来越多地应用于中医药研究中,可以恰当地评估中医药给患者带来的实际效益。然而,实效研究也存在诸多混杂和偏倚,如入选的研究对象与没有被入选者的特征不同所造成的选择偏倚;测量暴露或结局的方法有缺陷,使各比较组所获得的信息产生偏倚;有一个或多个混杂因素的影响,掩盖或夸大了研究因素与疾病(或事件)之间的联系所造成的混杂偏倚。尽管实效研究的兴起为临床研究开启了新天地,但如何应对实效研究中存在的偏倚,如何解读实效研究的结果都

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    2016-09-21 tinali1986

    好复杂,有点难

    0

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    2016-09-04 ylzr123

    赞!好文章,拜读,值得深入学习!

    0

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    2016-06-18 cathymary
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    2016-06-16 flyingzyx

    看得好晕

    0

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="mo">∑ni=1(Di–D¯)2. 上面的估计式也是通常的最小二乘解,这里只是换了一个推导方式。如果将 (1) 看成一个数据生成的机制,在假定 (2) 下我们的确可以估计出因果作用 β. 二 内生性和工具变量 问题的关键是假定 (2) 很多时候并不成立(cov(Di,εi)≠0),比如,吸烟的人群和不吸烟的人群本身很不相同,参加工作培训的人可能比不参加工作培训的人有更强的找工作动机,等