Objective: To define sample size requirements for establishing clinical serial monitoring protocols.
Design: The 95% confidence bound of a critical difference score is defined and used to identify false-negative regions suitable for sample size calculation.
Results: Reference subject sample sizes vary from about 40 to 480 subjects, depending on the minimum acceptable error rates of the clinical protocol.
Conclusions: Sample size requirements for establishing test–retest standards are generally defined and suitable for any serial monitoring protocol.
Serial monitoring is a commonly used clinical protocol whereby the change in a patient’s auditory function is compared with a reference test–retest standard. Minimum sample sizes needed to accurately estimate the reference test–retest standard must be established. This article provides a general solution to sample size requirements suitable for any quantitative metric.
1VA RR&D National Center for Rehabilitative Auditory Research (NCRAR), Portland VA, Medical Center, Portland, Oregon, USA; 2Oregon Health and Science University, Department of Public Health and Preventive Medicine, Portland, Oregon, USA; and 3Department of Statistics, University of South Carolina, 216 LeConte College Columbia, South Carolina, USA.
This article describes a simple method of determining sample sizes needed to establish clinical test–retest standards. This article expands on work published by Linnet (1987) by characterizing the sample size requirements in terms of the false-negative rate, which is suitable for any Gaussian data reference standard and easier to compute than methods proposed by Linnet. A variety of challenges remain. Non-Gaussian data, such as measurements with skewed distributions or step-like data such as pure-tone audiometry will require Gaussian transformation or nonparametric alternatives. In addition, audiologists regularly base their clinical judgment on the combined results of several tests. However, there is no accepted statistical method for combining screening tests, and thus no sample size formulae for efficiently generating multivariate reference standards. This situation is ubiquitous in laboratory medicine where sample size requirements based on univariate methods, such as are described in this article, are the standard for study design.
Kelly Reavis, Kristy Knight, and Marjorie Leek provided valuable advice on the development of this article.
The authors declare no conflict of interest.
Address for correspondence: Garnett P. McMillan, Portland VA Medical Center—NCRAR, 3710 US Veterans Hospital Road, P5, Portland, OR 97239, USA. E-mail: Garnett.firstname.lastname@example.org