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Multi-level models can benefit from minimizing higher-order variations: an illustration using child malnutrition data

机译:多级模型可从最小化高阶变化中受益:使用儿童营养不良数据的示意图

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This study aims to measure the robustness of multi-level models designed for three anthropometric indices - height-for-age (HAZ), weight-for-age (WAZ) and weight-for-height (WHZ) Z-scores for estimating the childhood malnutrition indicators stunting, underweight and wasting in Bangladesh. The 2011 BDHS child malnutrition data have been used in developing multi-level models with and without incorporating specific contextual variables relating to lower administrative units extracted from the 2011 Bangladesh Population and Housing Census. The robustness of the models is examined through (i) testing significance of random effects corresponding to lower administrative units through selection criteria including conditional AIC, R-squared, and LRT; (ii) comparing multi-level model-based estimators to design-based estimators of child malnutrition indicators with their precision at division, district and sub-district levels; and (iii) assessing the impact of contextual variables in capturing higher-order administrative level variations. Findings reveal that the inclusion of important contextual variables helps capture variations at higher-level administrative units, and consequently assists in the selection of robust multi-level models which ultimately provide improved accuracy of estimated parameters. The findings support the application of lower administrative census information in developing a simpler multi-level model by minimizing higher-order variation.
机译:这项研究旨在衡量针对三种人体测量指标设计的多级模型的鲁棒性-年龄高度(HAZ),年龄重量(WAZ)和体重高度(WHZ)Z得分,以估算孟加拉国儿童营养不良的发育不良,体重不足和浪费。 2011年BDHS儿童营养不良数据已用于开发多层次模型,有或没有纳入与从2011年孟加拉国人口和住房普查中提取的下级行政单位有关的具体背景变量。通过(i)通过条件AIC,R平方和LRT等选择标准测试与较低行政单位相对应的随机效应的重要性,从而检验模型的鲁棒性。 (ii)将基于模型的多层次估算器与基于设计的儿童营养不良指标估算器进行比较,其精度在分区,地区和分区级别; (iii)评估上下文变量对捕获更高级别的管理级别差异的影响。研究结果表明,重要的上下文变量的包含有助于捕获更高级别的管理部门的差异,因此有助于选择健壮的多级模型,从而最终提高估计参数的准确性。这些发现通过将较高阶的变化减到最小,支持了较低的行政普查信息在开发更简单的多层模型中的应用。

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