https://openalex.org/T10243
This cluster of papers focuses on various statistical methods and models for handling missing data in research, including multiple imputation, Bayesian modeling, generalized linear models, longitudinal data analysis, and sensitivity analysis. It covers topics such as model complexity, simulation studies, and the application of these methods in different fields. The cluster also discusses the challenges and best practices for analyzing datasets with missing values.
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rdfs:label "Methods for Handling Missing Data in Statistical Analysis"@en ;
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skos:definition "This cluster of papers focuses on various statistical methods and models for handling missing data in research, including multiple imputation, Bayesian modeling, generalized linear models, longitudinal data analysis, and sensitivity analysis. It covers topics such as model complexity, simulation studies, and the application of these methods in different fields. The cluster also discusses the challenges and best practices for analyzing datasets with missing values."@en ;
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openalex:cited_by_count 1144492 ;
openalex:works_count 25986 .