Yucel Recai M
Department of Epidemiology and Biostatistics, One University Place, Room 139, School of Public Health, University at Albany, SUNY, Rensselaer, NY 12144-3456, United States of America.
J Stat Softw. 2011 Dec;45(1). doi: 10.18637/jss.v045.i01.
Owing to its practicality as well as strong inferential properties, multiple imputation has been increasingly popular in the analysis of incomplete data. Methods that are not only computationally elegant but also applicable in wide spectrum of statistical incomplete data problems have also been increasingly implemented in a numerous computing environments. Unfortunately, however, the speed of this development has not been replicated in reaching to "sophisticated" users. While the researchers have been quite successful in developing the underlying software, documentation in a style that would be most reachable to the greater scientific society has been lacking. The main goal of this special volume is to close this gap by articles that illustrate these software developments. Here I provide a brief history of multiple imputation and relevant software and highlight the contents of the contributions. Potential directions for the future of the software development is also provided.
由于其实用性以及强大的推理特性,多重填补在不完全数据的分析中越来越受欢迎。那些不仅计算简洁而且适用于广泛统计不完全数据问题的方法,也在众多计算环境中得到了越来越多的应用。然而,不幸的是,这种发展速度在面向“复杂”用户方面却未能得到体现。虽然研究人员在开发底层软件方面相当成功,但却缺乏一种能被更广泛科学界最容易理解的文档风格。本特刊的主要目标是通过阐述这些软件开发的文章来弥合这一差距。在此,我简要介绍一下多重填补及相关软件的历史,并突出各篇稿件的内容。同时也提供了软件开发未来可能的方向。