Research Article Impact of Using Double Positive Samples in Deming Regression Samuel Akwasi Adarkwa , 1 Frank Kofi Owusu , 1 and Samuel Okyere 2 1 Department of Statistical Sciences, Kumasi Technical University, Kumasi, Ghana 2 Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana Correspondence should be addressed to Samuel Akwasi Adarkwa; saadarkwa@gmail.com Received 14 July 2022; Revised 20 July 2022; Accepted 22 July 2022; Published 12 August 2022 Academic Editor: Niansheng Tang Copyright © 2022 Samuel Akwasi Adarkwa et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In the method comparison approach, two measurement errors are observed. e classical regression approach (linear regression) method cannot be used for the analysis because the method may yield biased and inefficient estimates. In view of that, the Deming regression is preferred over the classical regression. e focus of this work is to assess the impact of censored data on the traditional regression, which deletes the censored observations compared to an adapted version of the Deming regression that takes into account the censored data. e study was done based on simulation studies with NLMIXED being used as a tool to analyse the data. Eight different simulation studies were run in this study. Each of the simulation is made up of 100 datasets with 300 observations. Simulation studies suggest that the traditional Deming regression which deletes censored observations gives biased estimates and a low coverage, whereas the adapted Deming regression that takes censoring into account gives estimates that are close to the true value making them unbiased and gives a high coverage. When the analytical error ratio is misspecified, the estimates are as well not reliable and biased. 1. Introduction A biological assay (Bioassay) is a scientific experiment where a substance of interest is introduced to a living organism to assess the effects of the substance introduced. In the area of drug development, a quantitative bioassay is when the effects of the substance introduced are quantified. e quantitative bioassay is mainly applied in drug de- velopment and environmental pollution assessment [1]. In order for a firm to receive approval from the Food and Drugs Administration (FDA) for a new medical mea- surement device or method, the firm must show that the new method target value is accurate as the old standard method (gold standard method) [2]. In an example, suppose this pharmaceutical company has two methods X and Y that could be used to measure the count of CD4+ in the blood of HIV patients. If there are some measurement errors associated with one method, which may be due to calibration or the way the scientist handled the device while taking the measurement, the classical regression approach or traditional regression approach is normally employed. In this approach, the least- squares (LS) method is usually used to find “good” esti- mators of the regression parameters, intercept (β 0 ) and slope (β 1 ) [3]. In the LS method, it is assumed that the measurements of one of the methods are without random errors, i.e., in the most familiar setting, X is measured without error and Y is a linear function of the X plus some random measurement error, which is conventionally as- sumed and modeled by a normal distribution [4]. However, in this same pharmaceutical company, two variables X and Y are to be fitted to a straight line to the data and the two variables have errors in them. We would be willing to have more clarification on the dataset, how it was collected and why there are errors in both X and Y. e scientist would be surprised with the kind of questions these statisticians would ask him because to him as a scientist, errors in both variables may seem to be quite trivial since all he may need is to see the straight line plotted to the data. Suppose, for example, the company has got in their possession a new method Y that said to give a better reading of the CD4+ count in the blood of the HIV patients. e Hindawi International Journal of Mathematics and Mathematical Sciences Volume 2022, Article ID 3984857, 8 pages https://doi.org/10.1155/2022/3984857