title,doi,url,abstract,journal,publication_year,pmid,arxiv
Multiple Imputation for Missing Data Using Factored Regression Modelwith the Implementation of Current Population , https://doi.org/10.32628/IJSRCSEIT, https://ijsrcseit.com/CSEIT183180, Missing value or data is a major issue in all fields. Many models and methods are supported to substitute the missing values. In this paper we promote the use of statistical methods for treating missing data that employ single- or multiple- imputation of missing values. Proposed a method called factored regression model to multiply impute missing values in such data sets by modelling the joint distribution of the variables in the data through a sequence of generalised linear models. Apply our model to protect confidentiality of the current population survey data by generating multiply imputed partially synthetic data sets. , International Journal of Scientific Research in Computer Science Engineering and Information Technology, 2018, CSEIT183180