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Edit and Imputation - vrdc cornell 2025

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The document discusses the importance of edit and imputation procedures in statistical analysis, particularly in handling missing data within public-use and restricted-access datasets. It outlines formal models for edits and imputations, differentiating between types of missing data (records and items) and various methods for addressing these issues, including multiple imputation techniques. The document emphasizes the necessity of robust editing processes to ensure data accuracy and consistency, providing examples from surveys like the SIPP and CPS to illustrate practical applications.

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