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Multiple Imputation and its Application (Hardcover)
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Multiple Imputation and its Application (Hardcover)
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A practical guide to analysing partially observed data. Collecting,
analysing and drawing inferences from data is central to research
in the medical and social sciences. Unfortunately, it is rarely
possible to collect all the intended data. The literature on
inference from the resulting incomplete data is now huge, and
continues to grow both as methods are developed for large and
complex data structures, and as increasing computer power and
suitable software enable researchers to apply these methods. This
book focuses on a particular statistical method for analysing and
drawing inferences from incomplete data, called Multiple Imputation
(MI). MI is attractive because it is both practical and widely
applicable. The authors aim is to clarify the issues raised by
missing data, describing the rationale for MI, the relationship
between the various imputation models and associated algorithms and
its application to increasingly complex data structures. Multiple
Imputation and its Application: * Discusses the issues raised by
the analysis of partially observed data, and the assumptions on
which analyses rest. * Presents a practical guide to the issues to
consider when analysing incomplete data from both observational
studies and randomized trials. * Provides a detailed discussion of
the practical use of MI with real-world examples drawn from medical
and social statistics. * Explores handling non-linear relationships
and interactions with multiple imputation, survival analysis,
multilevel multiple imputation, sensitivity analysis via multiple
imputation, using non-response weights with multiple imputation and
doubly robust multiple imputation. Multiple Imputation and its
Application is aimed at quantitative researchers and students in
the medical and social sciences with the aim of clarifying the
issues raised by the analysis of incomplete data data, outlining
the rationale for MI and describing how to consider and address the
issues that arise in its application.
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