Review of software and methods for recovering missing values in sociological data sets

Analysis of sociological data involves the study of large arrays of variables that may contain missing values. The presence of a significant number of incomplete records leads to distortion of the statistical analysis results, misinterpretation of modeling results. The article surveys software and mathematical methods designed to fill in the gaps in the data sets during sociological research. The mathematical nature, advantages and disadvantages of the most common methods of restoration of omissions used in solving practical problems are considered. An overview of modern software used to solve such problems is presented. A method for selecting the most efficient imputation algorithm was proposed.

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