Chapman Robert
Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, 625 North Michigan Avenue, Chicago, IL, 60601, USA.
J Patient Rep Outcomes. 2022 Jun 3;6(1):59. doi: 10.1186/s41687-022-00464-9.
BACKGROUND: The Patient-Reported Outcome Measurement Information System (PROMIS) was developed to reliably measure health-related quality of life using the patient's voice. To achieve these aims, PROMIS utilized Item Response Theory methods in its development, validation and implementation. PROMIS measures are typically scored using a specific method to calculate scores, called Expected A Posteriori estimation. BODY: Expected A Posteriori scoring methods are flexible, produce accurate scores and can be efficiently calculated by statistical software. This work seeks to make Expected A Posteriori scoring methods transparent and accessible to a larger audience through description, graphical demonstration and examples. Further applications and practical considerations of Expected A Posteriori scoring are presented and discussed. All materials used in this paper are made available through the R Markdown reproducibility framework and are intended to be reviewed and reused. Commented statistical code for the calculation of Expected A Posteriori scores is included. CONCLUSION: This work seeks to provide the reader with a summary and visualization of the operation of Expected A Posteriori scoring, as implemented in PROMIS. As PROMIS is increasingly adopted and implemented, this work will provide a basis for making psychometric methods more accessible to the PROMIS user base.
背景:患者报告结局测量信息系统(PROMIS)旨在通过患者的反馈来可靠地测量与健康相关的生活质量。为实现这些目标,PROMIS在其开发、验证和实施过程中采用了项目反应理论方法。PROMIS测量通常使用一种特定的方法来计算分数,即期望后验估计法。 主体:期望后验评分方法灵活,能产生准确的分数,并且可以通过统计软件高效计算。这项工作旨在通过描述、图形演示和示例,使期望后验评分方法对更广泛的受众来说更加透明和易于理解。文中还介绍并讨论了期望后验评分的进一步应用和实际考量。本文使用的所有材料都通过R Markdown可重复性框架提供,旨在供读者审阅和重复使用。文中包含了用于计算期望后验分数的带注释的统计代码。 结论:这项工作旨在为读者提供对PROMIS中实施的期望后验评分操作的总结和可视化。随着PROMIS越来越多地被采用和实施,这项工作将为使心理测量方法更易于PROMIS用户群体使用提供基础。
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