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Updated: Sep 19, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

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非线性孟德尔随机化:用模拟和实证实例评估残余和双排列方法中的效果修改

Fergus W Hamilton1,2, David A Hughes3, Tianyuan Lu4,5,6,7

  • 1MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK. fergus.hamilton@bristol.ac.uk.

European journal of epidemiology
|June 2, 2025
PubMed
概括

非线性门德尔随机化 (NLMR) 方法可以产生偏差的结果,由于遗传效应异质性. 研究人员发现,剩余和双排名的NLMR技术都容易受到不可预测的偏差的影响,因此在应用中需要谨慎.

关键词:
生物统计学 生物统计学门德尔的随机化方法 方法 方法这是NLMR的NLMR.

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