Nonparametric regression method for broad sense agreement

ABSTRACT

Characterising the correspondence between an ordinal measurement and a continuous measurement is often of interest in mental health studies. To this end Peng et al. [(2011), ‘A Framework for Assessing Broad Sense Agreement Between Ordinal and Continuous Measurements’, Journal of the American Statistical Association, 106, 1592–1601] introduced the concept of broad sense agreement (BSA) and developed nonparametric estimation and inference for a BSA measure. In this work, we propose a nonparametric 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 patients.

KEYWORDS:

• Broad sense agreement
• jackknife
• nonparametric regression
• U-statistic

AMS SUBJECT CLASSIFICATION:

• Primary: 62G08
• Secondary: 62G20

Acknowledgments

The authors thank Dr Tanja Jovanovic for providing the data set from the PTSD study and stimulating discussions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research is supported by the U.S. National Institutes of Health grants 5R01 MH079448-06 and 4R01 HL113548-05.