By Stef van Buuren
Missing facts shape an issue in each clinical self-discipline, but the recommendations required to deal with them are complex and sometimes missing. one of many nice rules in statistical science—multiple imputation—fills gaps within the info with believable values, the uncertainty of that's coded within the information itself. It additionally solves different difficulties, lots of that are lacking info difficulties in hide.
Flexible Imputation of lacking Data is supported by way of many examples utilizing actual facts taken from the author's immense event of collaborative study, and offers a realistic consultant for dealing with lacking info below the framework of a number of imputation. additionally, special information of implementation in R utilizing the author’s package deal MICE is incorporated in the course of the book.
Assuming familiarity with uncomplicated statistical ideas and multivariate tools, Flexible Imputation of lacking Data is meant for 2 audiences:
- (Bio)statisticians, epidemiologists, and methodologists within the social and overall healthiness sciences
- Substantive researchers who don't name themselves statisticians, yet who own the mandatory talents to appreciate the foundations and to keep on with the recipes
This graduate-tested publication avoids mathematical and technical information up to attainable: formulation are observed via a verbal assertion that explains the formulation in layperson phrases. Readers much less interested by the theoretical underpinnings may be in a position to choose up the overall notion, and technical fabric is obtainable if you happen to wish deeper figuring out. The analyses could be replicated in R utilizing a committed package deal constructed by way of the author.
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