在随机剂量比较试验中学习暴露-反应因果关系的工具变量方法

IF 1.5 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Statistics in Biopharmaceutical Research Pub Date : 2024-03-06 DOI:10.1080/19466315.2024.2327303
Zhiwei Zhang, Jixian Wang, Dong Xi
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引用次数: 0

摘要

我们考虑的问题是,在随机剂量比较试验中,如何估计药物暴露对临床反应的因果效应。因为暴露量是不确定的。
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An Instrumental Variable Approach to Learning the Causal Exposure-Response Relationship in a Randomized Dose Comparison Trial
We consider the problem of estimating the causal effect of drug exposure on clinical response in a randomized dose comparison trial where each group receives a different dose. Because exposure is n...
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来源期刊
Statistics in Biopharmaceutical Research
Statistics in Biopharmaceutical Research MATHEMATICAL & COMPUTATIONAL BIOLOGY-STATISTICS & PROBABILITY
CiteScore
3.90
自引率
16.70%
发文量
56
期刊介绍: Statistics in Biopharmaceutical Research ( SBR), publishes articles that focus on the needs of researchers and applied statisticians in biopharmaceutical industries; academic biostatisticians from schools of medicine, veterinary medicine, public health, and pharmacy; statisticians and quantitative analysts working in regulatory agencies (e.g., U.S. Food and Drug Administration and its counterpart in other countries); statisticians with an interest in adopting methodology presented in this journal to their own fields; and nonstatisticians with an interest in applying statistical methods to biopharmaceutical problems. Statistics in Biopharmaceutical Research accepts papers that discuss appropriate statistical methodology and information regarding the use of statistics in all phases of research, development, and practice in the pharmaceutical, biopharmaceutical, device, and diagnostics industries. Articles should focus on the development of novel statistical methods, novel applications of current methods, or the innovative application of statistical principles that can be used by statistical practitioners in these disciplines. Areas of application may include statistical methods for drug discovery, including papers that address issues of multiplicity, sequential trials, adaptive designs, etc.; preclinical and clinical studies; genomics and proteomics; bioassay; biomarkers and surrogate markers; models and analyses of drug history, including pharmacoeconomics, product life cycle, detection of adverse events in clinical studies, and postmarketing risk assessment; regulatory guidelines, including issues of standardization of terminology (e.g., CDISC), tolerance and specification limits related to pharmaceutical practice, and novel methods of drug approval; and detection of adverse events in clinical and toxicological studies. Tutorial articles also are welcome. Articles should include demonstrable evidence of the usefulness of this methodology (presumably by means of an application). The Editorial Board of SBR intends to ensure that the journal continually provides important, useful, and timely information. To accomplish this, the board strives to attract outstanding articles by seeing that each submission receives a careful, thorough, and prompt review. Authors can choose to publish gold open access in this journal.
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