Missing Data (Quantitative Applications in the Social Sciences)
Paul D. Allison presents practical techniques for managing missing data in social science research, focusing on multiple imputation and maximum-likelihood methods.
About This Book
This volume introduces methods for analyzing datasets that contain missing values.
It covers common patterns of missingness and the assumptions required by each technique.
Readers learn how to implement multiple imputation and maximum-likelihood procedures.
The text emphasizes practical application within widely used statistical software.
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