提高从混合样本推断的效率,以进行有效的健康监测调查:对定量方法的全面审查
Mansour Fahimi1, Elizabeth C Hair2, Elizabeth K Do2
1Marketing Systems Group, Horsham, PA, United States.
JMIR public health and surveillance
|March 7, 2024
概括
一种新的复合权重方法提供了一种更有效和更容易获得的方法来结合来自混合样本调查的数据,在计算方便性和推断准确性方面优于传统的复合估计.
科学领域:
- 调查方法调查方法.
- 统计推断的统计推断.
- 数据科学是数据科学.
背景情况:
- 混合样本,结合不同的数据源,越来越多地用于调查研究.
- 传统的综合估计用于汇集调查数据是计算密集的,并且具有推理限制.
- 混合调查数据的临时方法往往缺乏科学完整性,并可能导致误导性结果.
研究的目的:
- 审查传统的复合估计方法.
- 引入复合权重作为一种更有效的替代方案,用于汇集多项调查数据.
- 提供一种可访问的方法来改进混合样本调查的推断.
主要方法:
- 审查传统的复合估计.
- 综合权重的介绍和理论/实证证明.
- 使用三项混合样本调查数据的插图.
主要成果:
- 复合权重在计算上比传统的复合估计要求更低.
- 复合权重产生更有效的估计,具有更高的外部有效性.
- 建议的方法对从业人员来说更容易使用.
结论:
- 传统方法在数字时代面临挑战,原因是效率低下.
- 对混合样本的零碎方法是不够的.
- 复合权重为混合样本调查提供了持久且易于获得的解决方案.
关键词:
综合估计的综合估计.复合权重的权重是一个复合的权重.数据收集数据收集数据收集混合样本 混合样本最优的组合因子是最佳组合因子.风险因素的风险因素是什么采样调查调查的样本调查.监控监督监督监督监督监督监督监督监督监督监督监督监督监督监督监督监督监督不平等的权重影响不平等的权重影响.权衡权衡权衡权衡权衡权衡权衡权更多相关视频
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