Establishing reference interval bounds for censored and contaminated data

• Henrik Bruun, Niels ^[1] ; Uldall Torp, Nanna Maria ^[1] ; Linding Andersen, Stipe ^[2]
  1. [1] Research Data and Biostatistics Aalborg University Hospital Aalborg, Denmark
  2. [2] Department of Clinical Biochemistry Aalborg University Hospital Aalborg, Denmark and Department of Clinical Medicine Aalborg University Aalborg, Denmark
• Localización: The Stata journal, ISSN 1536-867X, Vol. 25, Nº. 1, 2025, págs. 151-168
• Idioma: inglés
• DOI: 10.1177/1536867X251322968
• Enlaces
  • Texto completo
• Resumen

  • Reference intervals are essential across the medical and environmental fields. A reference interval (for example, the central prediction interval) defines the normal range of measurements for a specific physiological parameter in healthy individuals. Inappropriate reference interval bounds may occur because of censored measurements (due to instrument limitations) or contaminated data (by accidentally sampling nonhealthy individuals). To address this, we propose using the regression-on-order-statistics (ROS) method combined with an optimal Box–Cox transformation. The ROS method involves regressing Gaussian scores based on ranks from ordered noncensored Box–Cox transformed measurements. To find the optimal Box–Cox transformation, we maximize the adjusted when estimating the mean and standard deviation through regression of empirical Gaussian quantiles on measurements. We demonstrate how to identify contamination and introduce a new command, ros. Real-life data illustrate the effectiveness of the ROS method.