From the late 15th century onwards, a flurry of voyages were made into the North Atlantic in search of fish, the fabled Northwest Passage, and beyond into the territories purely imaginary. Today, this vast expanse is crisscrossed with ocean and wind currents, submarine cables and wireless signals, seabirds and passengers, static and cargo ships. In her long-awaited poetry debut, award-winning digital writer and artist J.R. Carpenter transforms the dense, fragmented archive of the North Atlantic into an astonishing sea of fresh new text. Cartographic and maritime vernaculars inflected with the syntax and grammar of ships logs and code languages splinter and pulse across the page. Haunting, politically charged and formally innovative, An Ocean of Static presents an ever-shifting array of variables. Amid global currents of melting sea ice and changing ocean currents, Carpenter charts the elusive passages of women and animals, of indigenous people and migrants, of strange noises and phantom islands.

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.

This dictionary spans the practice of pharmacology, and of allied sciences insofar as they are related to it, with particular emphasis on the development, regulation and use of human medicine. It is offered to students as well as to professionals in pharmacology and allied sciences for "reference" and for "browsing," and as a bedside book and travelling companion. Its size (approximately 2000 entries) is appropriate for these uses.

Features of this dictionary:

- Provides definitions of terms in pharmacology, both basic and clinical

- Gives information on new medicine development and official regulations

- Covers allied topics, including statistics, ethics, scientific miscounduct, authorship, publication and law.