Statistical Analysis with Missing Data (3rd Edition) – eBook

Description

**Book Description:**

Delve into the critical and evolving field of missing data in statistics with the newly released **Third Edition** of a timeless classic. This meticulously revised textbook, authored by the esteemed scholars Donald Rubin and Roderick Little, offers a contemporary perspective on an increasingly important topic that has garnered significant attention over the past few decades.

**Statistical Analysis with Missing Data, 3rd Edition (PDF)** serves as a comprehensive guide that seamlessly intertwines theory and practical application. In this edition, Rubin and Little meticulously revisit historical methodologies while introducing simplified techniques for conducting multivariate analysis in the presence of missing values. The authors provide a sound theoretical framework, exploring likelihoods that stem from statistical models regarding both the existing data and the mechanisms behind the missing data. They apply these principles to address a variety of pressing missing data challenges, emphasizing real-world applicability.

Beginning with a foundational introduction, the text navigates through the complexities of missing data mechanisms and patterns, offering a detailed taxonomy. It further examines the implications of missing data in experimental contexts and elaborates on complete-case and available-case analyses, inclusive of innovative weighting techniques. This new edition broadens its scope to encompass contemporary advancements in the field, addressing topics such as nonresponse in sample surveys, diagnostic methodologies, causal inference, and sensitivity analyses, along with a plethora of other vital areas.

Highlights of the **3rd Edition** include:
– A thoroughly updated and expanded bibliography to support deeper exploration.
– Over 150 engaging exercises, integrating numerous new additions to challenge and enhance learning.
– Contributions from respected authorities, making this revised edition a definitive resource.
– Adjustments made based on feedback from students and educators, ensuring relevance and clarity.
– Insights into cutting-edge methods like multiple imputation, robust alternatives to weighting, and Bayesian approaches.

In recognition of their significant contributions to the field, the authors received The Karl Pearson Prize from the International Statistical Institute in 2017, acknowledging their profound influence on statistical methodology and application. Their work has been described as “defining and transformative” (ISI), underscoring the remarkable impact of their research.

**Statistical Analysis with Missing Data, 3rd Edition** is an invaluable textbook for upper-undergraduate and beginning graduate students alike, as well as a rich resource for applied practitioners and statisticians operating in both government sectors and industry.

**NOTE:** The product exclusively includes the eBook **Statistical Analysis with Missing Data, 3rd Edition in PDF format. Access codes are not provided.**

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