Related Experiment Video
Updated: Jun 12, 2026

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
Published on: August 9, 2024
Sample size calculations for evaluating a diagnostic test when the gold standard is missing at random
Andrzej S Kosinski1, Ying Chen, Robert H Lyles
1Department of Biostatistics and Bioinformatics, Duke University Medical Center, Duke Clinical Research Institute, P. O. Box 17969, Durham, NC 27715, USA. andrzej.kosinski@duke.edu
Abstract:
Performance of a diagnostic test is ideally evaluated by a comparison of the test results to a gold standard for all the patients in a study. In practice, however, it is common for a subset of study patients to have the gold standard not verified (missing) due to ethical or expense considerations. Sensitivity and specificity are often used as the relevant test performance measures and a joint confidence region (CR) for sensitivity and specificity can summarize the precision of estimates. In this paper, we present an approach to sample size computations when designing a study in which the gold standard is considered to be missing at random (MAR). We calculate the needed increase in sample size to ensure that the joint CR under MAR falls inside the boundaries of the joint CR derived for data with no missingness present.
Related Concept Videos
Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
Testing a Claim about Mean: Unknown Population SD
Estimating a population mean requires the samples to be approximately normally distributed. The data should be collected from the randomly selected samples having no sampling bias. There is no specific requirement for sample size. But if the sample size is less than 30, and we don't know the population standard deviation, a different approach is used; instead...
Accuracy and Errors in Hypothesis Testing
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5% chance...
Sample Size Calculation
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
Detection of Gross Error: The Q Test
Estimating Population Mean with Unknown Standard Deviation
William S. Gosset (1876–1937) of the Guinness...