Household survey data from the Demographic and Health Surveys (DHS) Program is published with GPS coordinates. However, almost all geostatistical analyses of such data ignore that the published GPS coordinates are randomly displaced (jittered). In this short report, we develop a geostatistical model that accounts for the positional uncertainty when analysing DHS surveys, and provide a fast implementation using Template Model Builder. The key focus is inference with Gaussian random fields under positional uncertainty, and our approach works for both Gaussian and non-Gaussian likelihoods. A simulation study with a binomial observation model shows that the new approach performs equally or better than the common approach of ignoring jittering, both in terms of more accurate parameter estimates and improved predictive measures. We demonstrate that the improvement would be larger under stronger jittering. An analysis of contraceptive use in Kenya shows that the approach is fast and easy to use in practice.
翻译:人口与健康调查(DHS)方案的家庭调查数据以GPS坐标公布,然而,几乎所有对这些数据的地理统计分析都忽略了已公布的GPS坐标是随机错位的(随机错位的 ) 。在本简短的报告中,我们开发了一个地理统计模型,在分析DHS调查时说明位置不确定性,并利用模版模型构建器提供快速实施。关键重点是在定位不确定性下与高斯随机字段的推论,以及我们对高斯人和非高斯人可能性的计算方法。用二元观察模型进行的模拟研究显示,新方法的表现与忽略倾斜的常见方法相同或更好,无论是在更准确的参数估计还是改进的预测措施方面都是如此。我们证明,改进的幅度将更大,在更强烈的振动下。对肯尼亚避孕药具使用情况的分析表明,该方法在实践上是快速和容易使用的。