论文标题
在三参数logistic模型中使用多个插补的小面积估计
Small area estimation using multiple imputation in three-parameter logistic models
论文作者
论文摘要
我们提出了一种新颖的方法，将项目响应理论方法与少量估计策略有关，在缺少数据的存在下。具体而言，我们为三参数logistic模型的平均能力参数提出了无偏估计器。因此，我们进行了一项广泛的仿真研究，以将我们的估计量与著名的Horvitz-Thompson估计器进行比较。根据我们对合成数据的实验，我们的建议与竞争对手相比，标准误差较低。此外，我们通过考虑2015年国际学生评估计划（PISA）的数学结果来执行实际应用，并将我们的结果与以前的分析进行比较。我们的发现强烈表明，我们的方法论是产生引人注目的官方统计数据的高竞争选择。
We propose a novel methodology relating item response theory methods with small area estimation strategies in the presence of missing data. Specifically, we propose an unbiased estimator for the average ability parameter of three-parameter logistic models. Thus, we carry out an extensive simulation study in order to compare our estimator with the well-known Horvitz-Thompson estimator. According to our experiments with synthetic data, our proposal has substantial lower standard errors than its competitor. In addition, we perform an actual application by considering the Mathematics results of the 2015 Program for International Student Assessment (PISA), and also, compare our results with previous analyses. Our findings strongly suggest that our methodology is a high competitive alternative for generating compelling official statistics.
