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[统计数据] 中重复二元结果的条件logistic估计 非顺应性双臂实验研究 [推广有奖]

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何人来此 在职认证  发表于 2022-4-4 13:55:00 来自手机 |只看作者 |坛友微信交流群|倒序 |AI写论文

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摘要翻译:
在双臂实验研究的因果模型下分析了条件logistic估计量的行为,其中可能有不依从性,治疗的效果是用二元反应变量来衡量的。我们表明,当仅在治疗组观察到不依从性时,在温和的条件下,治疗对依从性的影响和控制对不依从性的影响(用logit量表测量)可以被识别和一致地估计。对于控件对编译器的影响,情况却不是这样。然后提出一个简单的修正条件logistic估计量,使我们可以大大减少它的偏差估计这个数量和处理超过控制对编译者的因果影响。利用广义最大似然估计理论,研究了一个两步估计结果的渐近性质。通过仿真研究了该估计量的有限样本性质,并给出了对缺失响应情形的推广。该方法通过对一个数据集的应用来说明,该数据集来自一个关于乳房自我检查练习的培训课程的有效性的研究。
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英文标题:
《On the conditional logistic estimator for repeated binary outcomes in
  two-arm experimental studies with non-compliance》
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作者:
Francesco Bartolucci
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最新提交年份:
2008
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分类信息:

一级分类:Mathematics        数学
二级分类:Statistics Theory        统计理论
分类描述:Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计:例如统计推断、回归、时间序列、多元分析、数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
--
一级分类:Statistics        统计学
二级分类:Statistics Theory        统计理论
分类描述:stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近,贝叶斯推论,决策理论,估计,基础,推论,检验。
--

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英文摘要:
  The behavior of the conditional logistic estimator is analyzed under a causal model for two-arm experimental studies with possible non-compliance in which the effect of the treatment is measured by a binary response variable. We show that, when non-compliance may only be observed in the treatment arm, the effect (measured on the logit scale) of the treatment on compliers and that of the control on non-compliers can be identified and consistently estimated under mild conditions. The same does not happen for the effect of the control on compliers. A simple correction of the conditional logistic estimator is then proposed which allows us to considerably reduce its bias in estimating this quantity and the causal effect of the treatment over control on compliers. A two-step estimator results whose asymptotic properties are studied by exploiting the general theory on maximum likelihood estimation of misspecified models. Finite-sample properties of the estimator are studied by simulation and the extension to the case of missing responses is outlined. The approach is illustrated by an application to a dataset deriving from a study on the efficacy of a training course on the practise of breast self examination.
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PDF链接:
https://arxiv.org/pdf/710.2608
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关键词:logistic ogistic logisti logist logis effect compliers studies 数据 数量

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