Estimating and correcting 'missing' people with disabilities in Indonesian statistics: Improving understanding of health care use at a regional level

估计和纠正印度尼西亚统计数据中“缺失”的残疾人：提高对区域一级医疗保健使用情况的了解

• 批准号: 2817767
• 金额: --
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2817767
• 关键词: Estimating; correcting; missing; people; disabilities

There is a lack of information about people with disability (PWD) in Indonesia. Due to various reasons,including fear of stigma and unclear definitions of disability in many surveys, there is a largeunderreporting of the numbers of PWD across the country. This creates different issues: a lack of focus ingovernment policies, poor health services and a lack of visibility of PWD. The aim of this research is toimprove estimates of the level and characteristics of PWD in Indonesia. Further, to assess, test and applydifferent methods of survey and population-based data collection and statistical analyses for estimatingand correcting 'missing' and 'misclassified' PWD. This project will use a mixed-methods approach whichwill include qualitative semi-structured interviews with health professionals alongside statistical analysisof available data. First, bivariate analysis and regression techniques will be used to explore the PWD whoare 'missing' from the statistics. The project will then use new and innovative quantitative methods forthis specific substantive area of disability. Missing data will be investigated using advanced methods formissing data analysis such as multiple imputation for investigation of values missing not at random(MNAR). Monte Carlo simulations will also be used to create records for missing PWD in Indonesia.Regression analysis will be complemented by Latent Class Analysis (LCA) which will help to performclassifications of those "missing" and those "misclassified" after they have been imputed and this newsummary variable will allow for further investigation of characteristics of people in these importantcategories.

印度尼西亚缺乏关于残疾人的信息。由于各种原因，包括害怕污名化和许多调查中对残疾的定义不明确，全国各地的残疾人人数大量少报。这造成了不同的问题：政府政策缺乏重点，卫生服务差，残疾人缺乏可见度。本研究的目的是提高对印度尼西亚残疾人水平和特征的估计。此外，评估、测试和应用不同的调查方法和基于人口的数据收集和统计分析，以估计和纠正“缺失”和“错误分类”的残疾人。该项目将采用混合方法，包括与卫生专业人员进行定性半结构化访谈，以及对现有数据进行统计分析。首先，将使用双变量分析和回归技术来探索从统计中“缺失”的PWD。然后，该项目将对残疾问题这一具体的实质性领域采用新的和创新的量化方法。将使用形成缺失数据分析的先进方法研究缺失数据，例如用于研究非随机缺失值（MNAR）的多重插补。MonteCarlo模拟也将被用来创建记录失踪的PWD在印尼。回归分析将补充潜在类分析（LCA），这将有助于执行分类的那些“失踪”和那些“错误分类”后，他们已经填补和这个新的汇总变量将允许进一步调查的人在这些重要类别的特点。