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在研究数据的分析过程中进行盲法。

Blinding during the analysis of research data.

机构信息

Humanalysis, Inc., 75 Clinton Street, Saratoga Springs, NY 12866, United States.

出版信息

Int J Nurs Stud. 2011 May;48(5):636-41. doi: 10.1016/j.ijnurstu.2011.02.010. Epub 2011 Mar 1.

Abstract

Blinding in randomized controlled trials (RCTs) is a strategy that is widely endorsed as a method of reducing the biases that can result from people's awareness of study participants' treatment group status. Blinding of participants and interventionists is often impossible in nursing RCTs, but data analysts can almost always be blinded. Yet, such blinding seldom occurs, perhaps because of misperceptions about the objectivity of statistical analysis. Data analysts make many semi-subjective decisions about such issues as handling missing data, transforming variables, undertaking subgroup analysis, and selecting covariates. These decisions ideally should be made without the analyst's knowledge of how treatment groups are coded. Strategies for achieving blinding among data analysts are discussed.

摘要

在随机对照试验(RCTs)中,盲法是一种被广泛认可的方法,可以减少人们对研究参与者治疗组状况的意识所导致的偏差。在护理 RCTs 中,对参与者和干预者进行盲法通常是不可能的,但数据分析员几乎总是可以被盲法。然而,这种盲法很少发生,也许是因为人们对统计分析的客观性存在误解。数据分析员在处理缺失数据、转换变量、进行亚组分析和选择协变量等问题上做出许多半主观的决策。这些决策最好在分析员不知道治疗组编码的情况下做出。讨论了实现数据分析员盲法的策略。

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