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Flexible Imputation of Missing Data Second Edition

Flexible Imputation of Missing Data Second Edition

Missing 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 reader’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. | Flexible Imputation of Missing Data Second Edition

GBP 38.99
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Combatting Cyberbullying in Digital Media with Artificial Intelligence

Combatting Cyberbullying in Digital Media with Artificial Intelligence

Rapid advancements in mobile computing and communication technology and recent technological progress have opened up a plethora of opportunities. These advancements have expanded knowledge facilitated global business enhanced collaboration and connected people through various digital media platforms. While these virtual platforms have provided new avenues for communication and self-expression they also pose significant threats to our privacy. As a result we must remain vigilant against the propagation of electronic violence through social networks. Cyberbullying has emerged as a particularly concerning form of online harassment and bullying with instances of racism terrorism and various types of trolling becoming increasingly prevalent worldwide. Addressing the issue of cyberbullying to find effective solutions is a challenge for the web mining community particularly within the realm of social media. In this context artificial intelligence (AI) can serve as a valuable tool in combating the diverse manifestations of cyberbullying on the Internet and social networks. This book presents the latest cutting-edge research theoretical methods and novel applications in AI techniques to combat cyberbullying. Discussing new models practical solutions and technological advances related to detecting and analyzing cyberbullying is based on AI models and other related techniques. Furthermore the book helps readers understand AI techniques to combat cyberbullying systematically and forthrightly as well as future insights and the societal and technical aspects of natural language processing (NLP)-based cyberbullying research efforts. Key Features: Proposes new models practical solutions and technological advances related to machine intelligence techniques for detecting cyberbullying across multiple social media platforms. Combines both theory and practice so that readers (beginners or experts) of this book can find both a description of the concepts and context related to the machine intelligence. Includes many case studies and applications of machine intelligence for combating cyberbullying. | Combatting Cyberbullying in Digital Media with Artificial Intelligence

GBP 74.99
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Handbook of Statistics in Clinical Oncology

Handbook of Statistics in Clinical Oncology

Many new challenges have arisen in the area of oncology clinical trials. New cancer therapies are often based on cytostatic or targeted agents which pose new challenges in the design and analysis of all phases of trials. The literature on adaptive trial designs and early stopping has been exploding. Inclusion of high-dimensional data and imaging techniques have become common practice and statistical methods on how to analyse such data have been refined in this area. A compilation of statistical topics relevant to these new advances in cancer research this third edition of Handbook of Statistics in Clinical Oncology focuses on the design and analysis of oncology clinical trials and translational research. Addressing the many challenges that have arisen since the publication of its predecessor this third edition covers the newest developments involved in the design and analysis of cancer clinical trials incorporating updates to all four parts: Phase I trials: Updated recommendations regarding the standard 3 + 3 and continual reassessment approaches along with new chapters on phase 0 trials and phase I trial design for targeted agents. Phase II trials: Updates to current experience in single-arm and randomized phase II trial designs. New chapters include phase II designs with multiple strata and phase II/III designs. Phase III trials: Many new chapters include interim analyses and early stopping considerations phase III trial designs for targeted agents and for testing the ability of markers adaptive trial designs cure rate survival models statistical methods of imaging as well as a thorough review of software for the design and analysis of clinical trials. Exploratory and high-dimensional data analyses: All chapters in this part have been thoroughly updated since the last edition. New chapters address methods for analyzing SNP data and for developing a score based on gene expression data. In addition chapters on risk calculators and forensic bioinformatics have been added. Accessible to statisticians and oncologists interested in clinical trial methodology the book is a single-source collection of up-to-date statistical approaches to research in clinical oncology.

GBP 52.99
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