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Updated: Jul 4, 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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评估两个小样本对固定的效果标准错误和多层模型中的推理的两个小样本纠正,使用异种,不平衡,集群数据的多层模型

Yichi Zhang1, Mark H C Lai2

  • 1Department Psychology, University of Southern California, 3620 South McClintock Ave., Los Angeles, CA, 90089-1061, USA.

Behavior research methods
|February 6, 2024
PubMed
概括

调整后的集群强度标准错误 (CR-SEs) 提供了准确的推断,用于使用异种类型的集群数据进行多层次建模. 他们保持了I型错误率,并在随机斜率模型中使用时为集群间效应提供更高的功率.

关键词:
异性多样性 异性多样性多层次建模的多层次建模小小的样本,小的样本.不平衡的集群不平衡的集群差异估计估计差异估计.

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