ScholarGate
助手
Process / pipelineMissing data

MICE — 多变量链式方程填充

多变量链式方程填充 (MICE) 是一种处理多变量数据集中缺失数据的迭代程序。该算法由 Stef van Buuren 和 Karin Groothuis-Oudshoorn 通过 R 包 mice (2011) 引入,它使用一个独立的回归模型,以所有其他变量为条件来填充每个缺失的变量,并反复循环遍历变量,直到填充值收敛。其结果是 m 个完整的数据集,这些数据集被单独分析并使用 Rubin 的规则进行合并。

用 StatMind 应用即将推出视频即将推出Download slides

阅读完整方法

仅限会员

使用免费账户登录即可阅读本节。

登录

Method map

The neighbourhood of related methods — select a node to explore.

来源

  1. van Buuren, S., & Groothuis-Oudshoorn, K. (2011). mice: Multivariate imputation by chained equations in R. Journal of Statistical Software, 45(3), 1–67. DOI: 10.18637/jss.v045.i03

如何引用本页

ScholarGate. (2026, June 2). Multivariate Imputation by Chained Equations (MICE). ScholarGate. https://scholargate.app/zh/statistics/mice-imputation

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side

被引用于

ScholarGateMICE (Multivariate Imputation by Chained Equations (MICE)). 于 2026-06-15 检索自 https://scholargate.app/zh/statistics/mice-imputation · 数据集: https://doi.org/10.5281/zenodo.20539026