Multiple imputation of missing data with skip-pattern covariates: a comparison of alternative strategies

IF 1.1 4区数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Statistical Computation and Simulation Pub Date : 2023-12-18 DOI:10.1080/00949655.2023.2293124

Guangyu Zhang, Yulei He, Bill Cai, Chris Moriarity, Hee-Choon Shin, Van Parsons, Katherine E. Irimata

引用次数: 0

Abstract

Multiple imputation (MI) is a widely used approach to address missing data issues in surveys. Variables included in MI can have various distributional forms with different degrees of missingness. H...

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使用跳过模式协变量对缺失数据进行多重估算：替代策略比较

多重估算（MI）是一种广泛应用于解决调查中缺失数据问题的方法。多重估算中包含的变量可以有不同的分布形式和不同的缺失程度。H...

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来源期刊

Journal of Statistical Computation and Simulation 数学-计算机：跨学科应用

CiteScore

2.30

自引率

8.30%

发文量

156

审稿时长

4-8 weeks

期刊介绍： Journal of Statistical Computation and Simulation ( JSCS ) publishes significant and original work in areas of statistics which are related to or dependent upon the computer. Fields covered include computer algorithms related to probability or statistics, studies in statistical inference by means of simulation techniques, and implementation of interactive statistical systems. JSCS does not consider applications of statistics to other fields, except as illustrations of the use of the original statistics presented. Accepted papers should ideally appeal to a wide audience of statisticians and provoke real applications of theoretical constructions.