Abstract

This paper addresses the issue of estimating the population variance of a study character in the joint presence of random non-response and measurement errors and its application for estimating variations in biological data. Additional information on two highly positively correlated auxiliary variables has been incorporated to develop a general class of estimators under stratified two-phase sampling scheme. Its properties, in terms of bias and mean square error, have been examined. Optimum strata weights have been determined by employing suitable calibration techniques. Simulations using artificial data, as well as real data involving the variation in prostate specific antigen in different age groups when information about prostrate cancer volume and prostate weight is available, demonstrate the performance of the proposed class of estimators with respect to a contemporary estimator. Relevant R codes have been provided as Appendix.

摘要

本文讨论了在随机无响应和测量误差共同存在的情况下估计研究角色的总体方差的问题及其在估计生物学数据变化中的应用。关于两个高度正相关的辅助变量的附加信息已被并入，以在分层两阶段采样方案下开发出通用的估计量类别。已经检验了其特性（根据偏差和均方误差）。通过采用合适的校准技术可以确定最佳的地层重量。当可以获得有关前列腺癌体积和前列腺重量的信息时，使用人工数据以及涉及不同年龄组前列腺特异性抗原变化的真实数据进行模拟，证明拟议的估算器类别相对于现代估算器的性能。相关的R代码已作为附录提供。