Jointly modeling means and variances for nonlinear mixed effects models with measurement errors and outliers.

IF 1.4 4区 数学 Q3 BIOLOGY
Biometrics Pub Date : 2025-01-07 DOI:10.1093/biomtc/ujaf018
Qian Ye, Lang Wu, Viviane Dias Lima
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引用次数: 0

Abstract

In longitudinal data analyses, the within-individual repeated measurements often exhibit large variations and these variations appear to change over time. Understanding the nature of the within-individual systematic and random variations allows us to conduct more efficient statistical inferences. Motivated by human immunodeficiency virus (HIV) viral dynamic studies, we considered a nonlinear mixed effects model for modeling the longitudinal means, together with a model for the within-individual variances which also allows us to address outliers in the repeated measurements. Statistical inference was then based on a joint model for the mean and variance, implemented by a computationally efficient approximate method. Extensive simulations evaluated the proposed method. We found that the proposed method produces more efficient estimates than the corresponding method without modeling the variances. Moreover, the proposed method provides robust inference against outliers. The proposed method was applied to a recent HIV-related dataset, with interesting new findings.

具有测量误差和异常值的非线性混合效应模型的均值和方差联合建模。
在纵向数据分析中,个体内重复测量经常表现出很大的变化,这些变化似乎随时间而变化。了解个体内部系统和随机变化的本质使我们能够进行更有效的统计推断。受人类免疫缺陷病毒(HIV)病毒动力学研究的启发,我们考虑了一个非线性混合效应模型来模拟纵向均值,以及一个个体内方差模型,该模型也允许我们处理重复测量中的异常值。然后,统计推断基于均值和方差的联合模型,通过计算效率高的近似方法实现。大量的仿真评估了所提出的方法。我们发现,所提出的方法比没有对方差建模的相应方法产生更有效的估计。此外,该方法对异常值具有鲁棒性推断。将提出的方法应用于最近的hiv相关数据集,有了有趣的新发现。
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来源期刊
Biometrics
Biometrics 生物-生物学
CiteScore
2.70
自引率
5.30%
发文量
178
审稿时长
4-8 weeks
期刊介绍: The International Biometric Society is an international society promoting the development and application of statistical and mathematical theory and methods in the biosciences, including agriculture, biomedical science and public health, ecology, environmental sciences, forestry, and allied disciplines. The Society welcomes as members statisticians, mathematicians, biological scientists, and others devoted to interdisciplinary efforts in advancing the collection and interpretation of information in the biosciences. The Society sponsors the biennial International Biometric Conference, held in sites throughout the world; through its National Groups and Regions, it also Society sponsors regional and local meetings.
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