Rahman Akm Fazlur, Peng Limin, Manatunga Amita, Guo Ying
Department of Biostatistics and Bioinformatics, Emory University Atlanta, GA 30322, U.S.A.
J Nonparametr Stat. 2017;29(2):280-300. doi: 10.1080/10485252.2017.1303058. Epub 2017 Mar 17.
Characterizing the correspondence between an ordinal measurement and a continuous measurement is often of interest in mental health studies. To this end, Peng, Li, Guo, and Manatunga (2011) introduced the concept of broad sense agreement (BSA) and developed nonparametric estimation and inference for a BSA measure. In this work, we propose a non-parametric regression framework for BSA, which provides a robust tool to further investigate population heterogeneity in BSA. We develop inferential procedures including regression function estimation and hypothesis testing. Extensive simulation studies demonstrate satisfactory performance of the proposed method. We also apply the new method to a recent Grady Trauma Study and reveal an interesting impact of depression severity on the alignment between a self-reported symptom instrument and clinician diagnosis in posttraumatic stress disorder (PSTD) patients.
在心理健康研究中，刻画有序测量与连续测量之间的对应关系常常备受关注。为此，彭、李、郭和马纳通加（2011年）引入了广义一致性（BSA）的概念，并针对BSA度量开展了非参数估计与推断。在这项工作中，我们提出了一种用于BSA的非参数回归框架，它为进一步研究BSA中的总体异质性提供了一个强大的工具。我们开发了包括回归函数估计和假设检验在内的推断程序。大量的模拟研究表明所提方法具有令人满意的性能。我们还将这种新方法应用于最近的格雷迪创伤研究，揭示了抑郁严重程度对创伤后应激障碍（PSTD）患者自我报告症状工具与临床医生诊断之间一致性的有趣影响。
