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A Unified Approach to Power Calculation and Sample Size Determination for Random Regression Models

机译:随机回归模型的功效计算和样本大​​小确定的统一方法

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摘要

The underlying statistical models for multiple regression analysis are typically attributed to two types of modeling: fixed and random. The procedures for calculating power and sample size under the fixed regression models are well known. However, the literature on random regression models is limited and has been confined to the case of all variables having a joint multivariate normal distribution. This paper presents a unified approach to determining power and sample size for random regression models with arbitrary distribution configurations for explanatory variables. Numerical examples are provided to illustrate the usefulness of the proposed method and Monte Carlo simulation studies are also conducted to assess the accuracy. The results show that the proposed method performs well for various model specifications and explanatory variable distributions.
机译:多元回归分析的基础统计模型通常归因于两种类型的建模:固定模型和随机模型。在固定回归模型下计算功效和样本量的过程是众所周知的。但是,有关随机回归模型的文献有限,并且仅限于所有变量具有联合多元正态分布的情况。本文提出了一种确定随机回归模型的功效和样本量的统一方法,该模型具有用于解释变量的任意分布配置。数值例子说明了该方法的有效性,并进行了蒙特卡洛模拟研究以评估其准确性。结果表明,该方法在各种模型规范和解释变量分布方面表现良好。

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