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Bioinformatics in Human Health and Heredity
The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments. The Handbook of Statistics, a series of self-contained reference books. Each volume is devoted to a particular topic in statistics with Volume 28 dealing with bioinformatics. Every chapter is written by prominent workers in the area to which the volume is devoted. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. - Comprehensively presents the various aspects of statistical methodology - Discusses a wide variety of diverse applications and recent developments - Contributors are internationally renowned experts in their respective areas
Improving Crop Estimates by Integrating Multiple Data Sources
The National Agricultural Statistics Service (NASS) is the primary statistical data collection agency within the U.S. Department of Agriculture (USDA). NASS conducts hundreds of surveys each year and prepares reports covering virtually every aspect of U.S. agriculture. Among the small-area estimates produced by NASS are county-level estimates for crops (planted acres, harvested acres, production, and yield by commodity) and for cash rental rates for irrigated cropland, nonirrigated cropland, and permanent pastureland. Key users of these county-level estimates include USDA's Farm Services Agency (FSA) and Risk Management Agency (RMA), which use the estimates as part of their processes for dis...
Using Models to Estimate Hog and Pig Inventories
In 2014, the National Agricultural Statistics Service (NASS) engaged the National Academies of Sciences, Engineering, and Medicine to convene a planning committee to organize a public workshop for an expert open discussion of their then-current livestock models. The models had worked well for some time. Unfortunately beginning in 2013, an epidemic that killed baby pigs broke out in the United States. The epidemic was not fully realized until 2014 and spread to many states. The result was a decline in hog inventories and pork production that was not predicted by the models. NASS delayed the workshop until 2019 while it worked to develop models that could help in times both of equilibrium and shock (disease or disaster), as well as alternative approaches to help detect the onset of a shock. The May 15, 2019, workshop was consistent with NASS's 2014 intention, but with a focus on a model that can help predict hog inventories over time, including during times of shock. This publication summarizes the presentations and discussions from the workshop.
Practical Synthetic Data Generation
Building and testing machine learning models requires access to large and diverse data. But where can you find usable datasets without running into privacy issues? This practical book introduces techniques for generating synthetic data—fake data generated from real data—so you can perform secondary analysis to do research, understand customer behaviors, develop new products, or generate new revenue. Data scientists will learn how synthetic data generation provides a way to make such data broadly available for secondary purposes while addressing many privacy concerns. Analysts will learn the principles and steps for generating synthetic data from real datasets. And business leaders will s...
A Consumer Food Data System for 2030 and Beyond
Patterns of food consumption and nutritional intake strongly affect the population's health and well-being. The Food Economics Division of USDA's Economic Research Service (ERS) engages in research and data collection to inform policy making related to the leading federal nutrition assistance programs managed by USDA's Food and Nutrition Service. The ERS uses the Consumer Food Data System to understand why people choose foods, how food assistance programs affect these choices, and the health impacts of those choices. At the request of ERS, A Consumer Food Data System for 2030 and Beyond provides a blueprint for ERS's Food Economics Division for its data strategy over the next decade. This report explores the quality of data collected, the data collection process, and the kinds of data that may be most valuable to researchers, policy makers, and program administrators going forward. The recommendations of A Consumer Food Data System for 2030 and Beyond will guide ERS to provide and sustain a multisource, interconnected, reliable data system.
Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives
This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics and real-world examples which do not feature in many standard texts. The book is dedicated to Professor Don Rubin (Harvard). Don Rubin has made fundamental contributions to the study of missing data. Key features of the book include: Comprehensive coverage of an imporant area for both research and applications. Adopts a pragmatic approach to describing a wide range of intermediate and advanced statistical techniques. Covers key topics such as multiple imputation, propensity scores, instrumental variables and Bayesian inference. Includes a number of applications from the social and health sciences. Edited and authored by highly respected researchers in the area.
Monitoring Educational Equity
Disparities in educational attainment among population groups have characterized the United States throughout its history. Education is sometimes characterized as the "great equalizer," but to date, the country has not found ways to successfully address the adverse effects of socioeconomic circumstances, prejudice, and discrimination that suppress performance for some groups. To ensure that the pursuit of equity encompasses both the goals to which the nation aspires for its children and the mechanisms to attain those goals, a revised set of equity indicators is needed. Measures of educational equity often fail to account for the impact of the circumstances in which students live on their aca...
Campaigns and Voters in Developing Democracies
Voting behavior is informed by the experience of advanced democracies, yet the electoral context in developing democracies is significantly different. Civil society is often weak, poverty and inequality high, political parties ephemeral and attachments to them weak, corruption rampant, and clientelism widespread. Voting decisions in developing democracies follow similar logics to those in advanced democracies in that voters base their choices on group affiliation, issue positions, valence considerations, and campaign persuasion. Yet developing democracies differ in the weight citizens assign to these considerations. Where few social identity groups are politically salient and partisan attachments are sparse, voters may place more weight on issue voting. Where issues are largely absent from political discourse, valence considerations and campaign effects play a larger role. Campaigns and Voters in Developing Democracies develops a theoretical framework to specify why voter behavior differs across contexts.
Privacy in Statistical Databases
This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2006, held in December 2006 in Rome, Italy. The 31 revised full papers are organized in topical sections on methods for tabular protection, utility and risk in tabular protection, methods for microdata protection, utility and risk in microdata protection, protocols for private computation, case studies, and software.
