Missing data imputation of questionnaires by means of genetic algorithms with different fitness functions

作者：

Highlights：

• A genetic algorithm for missing data imputation is proposed.

• The algorithm is tested in the context of the item response theory.

• Optimum parameters of the algorithm are analyzed.

• The proposed algorithm performs better than MICE algorithm.

摘要

•A genetic algorithm for missing data imputation is proposed.•The algorithm is tested in the context of the item response theory.•Optimum parameters of the algorithm are analyzed.•The proposed algorithm performs better than MICE algorithm.

论文关键词：Imputation method,Item response theory,Genetic algorithms,Multivariate imputation by chained equations (MICE),Missing data

论文评审过程：Received 9 November 2015, Revised 7 August 2016, Available online 31 August 2016, Version of Record 2 October 2016.

论文官网地址：https://doi.org/10.1016/j.cam.2016.08.012