02029cam a22002058i 4500008004100000020001800041042000800059082001800067100002100085245004000106250000900146260002800155300003000183504005100213520145500264650002801719650002601747650002501773650002501798180412s2019 flu b 001 0 eng a9781138588318 apcc a519.535bB8F5 aBuuren, Stef van aFlexible imputation of missing data a2nd. aLondonbCRC Pressc2018 axxvii, 415 p.bWith index aIncludes bibliographical references and index. aMissing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem.
This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field.
This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the readerâ€™s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.
https://www.crcpress.com/Flexible-Imputation-of-Missing-Data-Second-Edition/Buuren/p/book/9781138588318 aMathematical statistics aMultivariate analysis aMultiple imputation aMissing observations