Document Type
Article
Publication Date
2019
Publication Title
International Journal of Statistics and Probability
Abstract
In medical, health, and sports sciences, researchers desire a device with high reliability and validity. This article focuses on reliability and validity studies with n subjects and m ≥ 2 repeated measurements per subject. High statistical power can be achieved by increasing n or m, and increasing m is often easier than increasing n in practice unless m is too high to result in systematic bias. The sequential probability ratio test (SPRT) is a useful statistical method which can conclude a null hypothesis H0 or an alternative hypothesis H1 with 50% of the required sample size of a non-sequential test on average. The traditional SPRT requires the likelihood function for each observed random variable, and it can be a practical burden for evaluating the likelihood ratio after each observation of a subject. Instead, m observed random variables per subject can be transformed into a test statistic which has a known sampling distribution under H0 and under H1. This allows us to formulate a SPRT based on a sequence of test statistics. In this article, three types of study are considered: reliability of a device, reliability of a device relative to a criterion device, and validity of a device relative to a criterion device. Using SPRT for testing the reliability of a device, for small m, results in an average sample size of about 50% of the fixed sample size for a non-sequential test. For comparing a device to criterion, the average sample size approaches to 60% approximately as m increases. The SPRT tolerates violation of normality assumption for validity study, but it does not for reliability study.
Recommended Citation
Kim, Steven B. and Wand, Jeffrey O., "Sequential Testing in Reliability and Validity Studies With Repeated Measurements per Subject" (2019). Mathematics and Statistics Faculty Publications and Presentations. 5.
https://digitalcommons.csumb.edu/math_fac/5
Comments
Copyright for this article is retained by the author(s), with first publication rights granted to the journal.
This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
Published in International Journal of Statistics and Probability by the Canadian Center of Science and Education (CCSE). Available via doi: 10.5539/ijsp.v8n1p120.