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The goal of this book is to put an array of tools at the fingertips of students, practitioners, and researchers by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This volume serves at least three audiences: (1) students of applied sampling techniques; 2) practicing survey statisticians applying concepts learned in theoretical or applied sampling courses; and (3) social scientists and other survey practitioners who design, select, and weight survey samples. The text thoroughly covers fundamental aspects of survey sampling, such as sample size calculation (with examples for both single- and multi-stage sample design) and weight computation, accompanied by software examples to facilitate implementation. Features include step-by-step instructions for calculating survey weights, extensive real-world examples and applications, and representative programming code in R, SAS, and other packages. Since the publication of the first edition in 2013, there have been important developments in making inferences from nonprobability samples, in address-based sampling (ABS), and in the application of machine learning techniques for survey estimation. New to this revised and expanded edition: • Details on new functions in the PracTools package • Additional machine learning methods to form weighting classes • New coverage of nonlinear optimization algorithms for sample allocation • Reflecting effects of multiple weighting steps (nonresponse and calibration) on standard errors • A new chapter on nonprobability sampling • Additional examples, exercises, and updated references throughout Richard Valliant, PhD, is Research Professor Emeritus at the Institute for Social Research at the University of Michigan and at the Joint Program in Survey Methodology at the University of Maryland. He is a Fellow of the American Statistical Association, an elected member of the International Statistical Institute, and has been an Associate Editor of the Journal of the American Statistical Association, Journal of Official Statistics, and Survey Methodology. Jill A. Dever, PhD, is Senior Research Statistician at RTI International in Washington, DC. She is a Fellow of the American Statistical Association, Associate Editor for Survey Methodology and the Journal of Official Statistics, and an Assistant Research Professor in the Joint Program in Survey Methodology at the University of Maryland. She has served on several panels for the National Academy of Sciences and as a task force member for the American Association of Public Opinion Research’s report on nonprobability sampling. Frauke Kreuter, PhD, is Professor and Director of the Joint Program in Survey Methodology at the University of Maryland, Professor of Statistics and Methodology at the University of Mannheim, and Head of the Statistical Methods Research Department at the Institute for Employment Research (IAB) in Nürnberg, Germany. She is a Fellow of the American Statistical Association and has been Associate Editor of the Journal of the Royal Statistical Society,Journal of Official Statistics, Sociological Methods and Research, Survey Research Methods, Public Opinion Quarterly, American Sociological Review, and the Stata Journal. She is founder of the International Program for Survey and Data Science and co-founder of the Coleridge Initiative.

Statistics . --- Statistics for Social Sciences, Humanities, Law. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Statistical Theory and Methods.

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Von den Grundlagen bis zur Doktorarbeit Wie gut wirkt ein Medikament? Wie groß muss eine Stichprobe sein, um eine präzise Schätzung abgeben zu können? Wie führe ich eine Studie durch? Mit der Medizinischen Statistik lernen Sie,  Daten zu strukturieren, Zusammenhänge aufzudecken und Ergebnisse zu interpretieren. Und dabei müssen Sie weder Formeln auswendig lernen noch herleiten – die Grundlagen sind viel einfacher zu verstehen, als Sie vermuten!  Und das Basiswissen hilft Ihnen dabei: - Einfache Beispiele erklären die wichtigsten statistischen Anwendungen - Inhalte, die über das Basiswissen hinausgehen, sind markiert - Umfassender Überblick über klinische und epidemiologische Studien - Glossar Englisch-Deutsch für Paper und Statistiksoftware - Zur Prüfungsvorbereitung und als Nachschlagewerk Mit dem Basiswissen Medizinische Statistik überlassen Sie nichts dem Zufall.

Medicine. --- Health informatics. --- Epidemiology. --- Statistics . --- Medicine/Public Health, general. --- Health Informatics. --- Epidemiology. --- Statistics for Life Sciences, Medicine, Health Sciences.

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Dieses Buch liefert eine anwendungsorientierte Einführung in die Datenauswertung mit der freien Statistikumgebung R. Es behandelt deskriptive Auswertungen ebenso umfassend wie inferenzstatistische Analysen. Neben klassischen univariaten Verfahren berücksichtigt das Buch nonparametrische Tests, Resampling-Methoden und multivariate Statistik. Zudem deckt es die vielfältigen Möglichkeiten ab, Daten aufzubereiten und Diagramme zu erstellen. Die statistischen Verfahren werden anhand von Beispielen erläutert und an vielen Stellen mit Diagrammen illustriert. Das Buch richtet sich an alle, die R kennenlernen und in konkreten Aufgabenstellungen einsetzen möchten, ohne bereits über Vorerfahrungen mit befehlsgesteuerten Programmen oder Programmiersprachen zu verfügen. In die vierte Auflage sind sowohl die Neuerungen von R 3.3.2 als auch jüngere Entwicklungen bei den Zusatzpaketen eingeflossen. Gleichzeitig wurde der Text überarbeitet und um ein eigenes Kapitel zu Diagrammen mit ggplot2 erweitert. Der Text behandelt nun auch allgemeine numerische Methoden wie Nullstellensuche, numerische Integration und Ableitung sowie numerische Optimierung. Der Autor Dr. Daniel Wollschläger lehrte viele Jahre am Institut für Psychologie der Christian-Albrechts-Universität zu Kiel und ist nun am Institut für Medizinische Biometrie, Epidemiologie und Informatik der Johannes Gutenberg-Universität in Mainz tätig.

Statistics . --- Statistics and Computing/Statistics Programs. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Statistics for Social Sciences, Humanities, Law.

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The Handbook of Health Services Research is a reference for all aspects of the field of health services and outcomes research. It addresses the increasing need for comprehensive, yet balanced, information in a field that welcomes various disciplines: medicine, public health, statistics, economics, management, policy, and information technology. This well-organized reference is an indispensable source of information for everyone who seeks to develop understanding of health systems and to learn about historical, political, and socioeconomic factors that influence health policies at the global, national, regional and local level. Specifically, the Handbook helps readers: Recognize core concepts of health services and outcomes research, such as, need, access, equity, quality and safety; Become familiar with social, political, organizational, behavioral and economic theories that have influenced health systems designs; Learn about frameworks developed for evaluating the organization, financing, delivery, utilization and outcomes of health services; Get an introduction to methods of comparative effectiveness research, program evaluation, health technology assessment and health economics; Identify types and sources of data appropriate for generating valid and reliable information about the delivery of health services; Learn about strengths and weaknesses of various research designs used to study health services and policy issues. The online version of the Handbook of Health Services Research is in the format of a dynamically updated knowledge base, offering search tools, cross-referencing across chapters and linking to supplement data, other major reference works and external articles. The Handbook of Health Services Research is accessible at the level of graduate students even if it is not their focus area. This includes students with various backgrounds: medicine, public health, statistics, economics, management or information technology.

Health administration. --- Social policy. --- Statistics . --- Public health. --- Health Administration. --- Social Policy. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Public Health.

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The Handbook of Health Services Research is a reference for all aspects of the field of health services and outcomes research. It addresses the increasing need for comprehensive, yet balanced, information in a field that welcomes various disciplines: medicine, public health, statistics, economics, management, policy, and information technology. This well-organized reference is an indispensable source of information for everyone who seeks to develop understanding of health systems and to learn about historical, political, and socioeconomic factors that influence health policies at the global, national, regional and local level. Specifically, the Handbook helps readers: Recognize core concepts of health services and outcomes research, such as, need, access, equity, quality and safety; Become familiar with social, political, organizational, behavioral and economic theories that have influenced health systems designs; Learn about frameworks developed for evaluating the organization, financing, delivery, utilization and outcomes of health services; Get an introduction to methods of comparative effectiveness research, program evaluation, health technology assessment and health economics; Identify types and sources of data appropriate for generating valid and reliable information about the delivery of health services; Learn about strengths and weaknesses of various research designs used to study health services and policy issues. The online version of the Handbook of Health Services Research is in the format of a dynamically updated knowledge base, offering search tools, cross-referencing across chapters and linking to supplement data, other major reference works and external articles. The Handbook of Health Services Research is accessible at the level of graduate students even if it is not their focus area. This includes students with various backgrounds: medicine, public health, statistics, economics, management or information technology.

Health administration. --- Social policy. --- Statistics . --- Public health. --- Health Administration. --- Social Policy. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Public Health.