Literature DB >> 32494095

How to Optimize Measurement Protocols: An Example of Assessing Measurement Reliability Using Generalizability Theory.

Anthony A Gatti1, Paul W Stratford1, Nicholas M Brisson1,2, Monica R Maly1,3.   

Abstract

Purpose: This article identifies how to assess multiple sources of measurement error and identify optimal measurement strategies for obtaining clinical outcomes. Method: Obtaining, interpreting, and using information gained from measurements is instrumental in physiotherapy. To be useful, measurements must have a sufficiently small measurement error. Traditional expressions of reliability include relative reliability in the form of an intra-class correlation coefficient and absolute reliability in the form of the standard error of measurement. Traditional metrics are limited to assessing one source of error; however, real-world measurements consist of many sources of error. The measurement framework generalizability theory (GT) allows researchers to partition measurement errors into multiple sources. GT further allows them to calculate the relative and absolute reliability of any measurement strategy, thereby allowing them to identify the optimal strategy. We provide a brief comparison of classical test theory and GT, followed by an overview of the terminology and methodology used in GT, and then an example showing how GT can be used to minimize error associated with measuring knee extension power.
Conclusion: The methodology described provides tools for researchers and clinicians that enable detailed interpretation and understanding of the error associated with their measurements. © Canadian Physiotherapy Association.

Keywords:  biostatistics; biostatistique; outcome and process assessment, health care; recherche en réadaptation; rehabilitation research; reproducibility of results; reproductibilité des résultats; spécialité de la physiothérapie; évaluation des résultats

Year:  2020        PMID: 32494095      PMCID: PMC7238938          DOI: 10.3138/ptc-2018-0110

Source DB:  PubMed          Journal:  Physiother Can        ISSN: 0300-0508            Impact factor:   1.037


  2 in total

1.  Generalizability theory for the perplexed: a practical introduction and guide: AMEE Guide No. 68.

Authors:  Ralph Bloch; Geoffrey Norman
Journal:  Med Teach       Date:  2012       Impact factor: 3.650

2.  Generalizability theory: a practical guide to study design, implementation, and interpretation.

Authors:  Amy M Briesch; Hariharan Swaminathan; Megan Welsh; Sandra M Chafouleas
Journal:  J Sch Psychol       Date:  2013-12-26
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.