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Updated: May 30, 2025

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多变量受污染的正常线性混合模型应用于阿尔茨海默病研究,其中包含被审查和缺失的数据

Tsung-I Lin1,2, Wan-Lun Wang3

  • 1Institute of Statistics, National Chung Hsing University, Taichung, Taiwan.

Statistical methods in medical research
|January 31, 2025
PubMed
概括

这项研究引入了一个新的统计模型,有效地分析复杂的纵向临床数据,即使有异常值,缺失或被审查的值. 多变量受污染的正常线性混合模型 (MCNLMM-CM) 提高了数据分析的准确性.

关键词:
阿尔茨海默病神经成像倡议研究研究被审查的数据是被审查的数据.间歇性的失踪情况.轻微的异常值是轻微的异常值.多变量纵向数据多变量纵向数据

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