Abstract
The problem of assessing agreement between two devices occurs with great frequency in the medical literature. If it can be demonstrated that a new device agrees sufficiently with a device currently in use, then the new device can be approved for general use. This work discusses how a prediction interval can be used to estimate the whether a future difference between two devices will be within acceptable limits with reasonable confidence. The method is illustrated with an example involving measurements of peak expiratory flow.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Neder JA, Stein R. A simplified strategy for the estimation of the exercise ventilatory thresholds. Med Sci Sports Exerc. 2006;38:1007–13.
McGaughran L, Voss LJ, Oliver R, Petcu M, Schaare P, Barnard JPM, et al. Rapid measurement of blood propofol levels: a proof of concept study. J Clin Monit Comput. 2006;20:109–15.
Choudhary PK, Nagaraja HN. Measuring agreement in method comparison studies—a review. In: Balakrishnan N, Kannan N, Najaraja HN, editors. Advances in ranking and section, multiple comparisons, and reliability. Boston: Birkhauser, pp. 215–44.
Barnhart HX, Haber MJ, Lin LI. An overview on assessing agreement with continuous measurements. J Biopharm Stat. 2007;17:529–69.
Fleiss JL. The design and analysis of clinical experiments. New York, NY: Wiley.
St. Laurent RT. Evaluating agreement with a gold standard in method comparison studies. Biometrics. 1998;54:537–45.
Lin LI. A concordance correlation coefficient to evaluate reproducibility. Biometrics. 1989;45:255–68.
Muller R, Buttner P. A critical discussion of intraclass correlation coefficients. Stat Med. 1994;13:2465–76.
Lin LI. Total deviation index for measuring individual agreement with applications in laboratory performance and bioequivalence. Stat Med. 2000;30:255–70.
Lin LI, Hedayat AS, Sinha B, Yang M. Statistical methods in assessing agreement: models, issues and tools. J Am Stat Assoc. 2002;97:257–70.
Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;i:307–10.
Liu J, Chow SC. A two-one-sided tests procedure for assessment of individual bioequivalence. J Biopharm Stat. 1997;7:49–61.
Hamilton C, Stamey J. Using Bland–Altman to assess agreement between two medical devices—don’t forget the confidence intervals. J Clin Monit Comput. 2007;21:331–3.
Bland JM, Altman DG. Agreement between methods of measurement with multiple observation per individual. J Biopharm Stat. 2007;17:571–82.
Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res. 1999;8:135–60.
Author information
Authors and Affiliations
Corresponding author
Additional information
Hamilton C, Stamey JD. Using a prediction approach to assess agreement between two continuous measurements.
Rights and permissions
About this article
Cite this article
Hamilton, C., Stamey, J.D. Using a prediction approach to assess agreement between two continuous measurements. J Clin Monit Comput 23, 311–314 (2009). https://doi.org/10.1007/s10877-009-9198-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10877-009-9198-4