A permutation test to analyse systematic bias and random measurement errors of medical devices via boosting location and scale models. (June 2017)

• Record Type: Journal Article
• Authors: Mayr, Andreas; Schmid, Matthias; Pfahlberg, Annette; Uter, Wolfgang; Gefeller, Olaf
• Is Part Of: Statistical methods in medical research. Volume 26:Number 3(2017)
• Page Start: 1443
• Page End: 1460
• Publication Date: 2017-06
• Subjects: Measurement errors -- systematic bias -- random error -- statistical models -- permutation test -- gradient boosting -- regression; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280215581855
• Languages: English
• ISSNs: 0962-2802

Abstract

Measurement errors of medico-technical devices can be separated into systematic bias and random error. We propose a new method to address both simultaneously via generalized additive models for location, scale and shape (GAMLSS) in combination with permutation tests. More precisely, we extend a recently proposed boosting algorithm for GAMLSS to provide a test procedure to analyse potential device effects on the measurements. We carried out a large-scale simulation study to provide empirical evidence that our method is able to identify possible sources of systematic bias as well as random error under different conditions. Finally, we apply our approach to compare measurements of skin pigmentation from two different devices in an epidemiological study.