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Updated: Mar 6, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Incorporation of hierarchical structure into estimation and projection package fitting with examples of estimating
Xiaoyue Niu1, Amy Zhang, Tim Brown
1aDepartment of Statistics, Pennsylvania State University, University Park, Pennsylvania bEast-West Center, Honolulu, Hawaii, USA cStrategic Information and Evaluation Department, UNAIDS, Geneva, Switzerland.
Objectives:
The article aims to give Spectrum/estimation and projection package (EPP) users and the scientific community a basic understanding of the underlying statistical model used to incorporate hierarchical structure in HIV subnational estimation, and to show how it has been implemented in the Spectrum/EPP interface for improving subepidemic estimation. The article also provides recommended default settings for this new model.
Methods:
We apply a generalized linear mixed-effects model on antenatal clinics prevalence data to get area-specific prevalence and uncertainty estimates, and transform those estimates to auxiliary data. We then fit the EPP model to both the observed data and auxiliary data.
Results:
We apply the proposed methods to four countries with different levels of data availability. We compare the out-of-sample prediction accuracy of the proposed method with varying auxiliary sample sizes and EPP without auxiliary data.
Conclusion:
We find that borrowing information from data-rich areas to data-sparse areas using our proposed method improves EPP fit in data-sparse areas. We recommend using the sample size estimated from generalized linear mixed-effects model as the default auxiliary sample size.
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