Imputation adjustment method for missing data
Jin Yong
Abstract
Jin Yong
Abstract
Imputation is another sort of adjustment methods to reduce the bias of estimation under missing data. This paper introduces several imputation methods:those methods include: Deductive imputation, Mean value imputation, Randomized imputation Regression method and Multiple imputation.
OpenAlex reports 6 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Imputation is another sort of adjustment methods to reduce the bias of estimation under missing data. This paper introduces several imputation methods:those methods include: Deductive imputation, Mean value imputation, Randomized imputation Regression method and Multiple imputation.
Key concepts: Imputation (statistics), Missing data, Computer science, Statistics, Regression, Econometrics, Data mining, Mathematics