Applied Survey Data Analysis

Author: Steven G. Heeringa
Editor: CRC Press
ISBN: 1351649302
Size: 12,71 MB
Format: PDF, ePub, Mobi
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Highly recommended by the Journal of Official Statistics, The American Statistician, and other journals, Applied Survey Data Analysis, Second Edition provides an up-to-date overview of state-of-the-art approaches to the analysis of complex sample survey data. Building on the wealth of material on practical approaches to descriptive analysis and regression modeling from the first edition, this second edition expands the topics covered and presents more step-by-step examples of modern approaches to the analysis of survey data using the newest statistical software. Designed for readers working in a wide array of disciplines who use survey data in their work, this book continues to provide a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. An example-driven guide to the applied statistical analysis and interpretation of survey data, the second edition contains many new examples and practical exercises based on recent versions of real-world survey data sets. Although the authors continue to use Stata for most examples in the text, they also continue to offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book’s updated website.

Applied Survey Data Analysis

Author: Steven G. Heeringa
Editor: CRC Press
ISBN: 9781420080674
Size: 15,79 MB
Format: PDF
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Taking a practical approach that draws on the authors’ extensive teaching, consulting, and research experiences, Applied Survey Data Analysis provides an intermediate-level statistical overview of the analysis of complex sample survey data. It emphasizes methods and worked examples using available software procedures while reinforcing the principles and theory that underlie those methods. After introducing a step-by-step process for approaching a survey analysis problem, the book presents the fundamental features of complex sample designs and shows how to integrate design characteristics into the statistical methods and software for survey estimation and inference. The authors then focus on the methods and models used in analyzing continuous, categorical, and count-dependent variables; event history; and missing data problems. Some of the techniques discussed include univariate descriptive and simple bivariate analyses, the linear regression model, generalized linear regression modeling methods, the Cox proportional hazards model, discrete time models, and the multiple imputation analysis method. The final chapter covers new developments in survey applications of advanced statistical techniques, including model-based analysis approaches. Designed for readers working in a wide array of disciplines who use survey data in their work, this book also provides a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. A guide to the applied statistical analysis and interpretation of survey data, it contains many examples and practical exercises based on major real-world survey data sets. Although the authors use Stata for most examples in the text, they offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book’s website: http://www.isr.umich.edu/src/smp/asda/

Complex Survey Data Analysis With Sas

Author: Taylor H. Lewis
Editor: CRC Press
ISBN: 1315349779
Size: 14,30 MB
Format: PDF, Kindle
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Complex Survey Data Analysis with SAS® is an invaluable resource for applied researchers analyzing data generated from a sample design involving any combination of stratification, clustering, unequal weights, or finite population correction factors. After clearly explaining how the presence of these features can invalidate the assumptions underlying most traditional statistical techniques, this book equips readers with the knowledge to confidently account for them during the estimation and inference process by employing the SURVEY family of SAS/STAT® procedures. The book offers comprehensive coverage of the most essential topics, including: Drawing random samples Descriptive statistics for continuous and categorical variables Fitting and interpreting linear and logistic regression models Survival analysis Domain estimation Replication variance estimation methods Weight adjustment and imputation methods for handling missing data The easy-to-follow examples are drawn from real-world survey data sets spanning multiple disciplines, all of which can be downloaded for free along with syntax files from the author’s website: http://mason.gmu.edu/~tlewis18/. While other books may touch on some of the same issues and nuances of complex survey data analysis, none features SAS exclusively and as exhaustively. Another unique aspect of this book is its abundance of handy workarounds for certain techniques not yet supported as of SAS Version 9.4, such as the ratio estimator for a total and the bootstrap for variance estimation. Taylor H. Lewis is a PhD graduate of the Joint Program in Survey Methodology at the University of Maryland, College Park, and an adjunct professor in the George Mason University Department of Statistics. An avid SAS user for 15 years, he is a SAS Certified Advanced programmer and a nationally recognized SAS educator who has produced dozens of papers and workshops illustrating how to efficiently and effectively conduct statistical analyses using SAS.

Applied Survey Methods

Author: Jelke Bethlehem
Editor: John Wiley & Sons
ISBN: 9780470494981
Size: 17,35 MB
Format: PDF, ePub, Docs
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A complete, hands-on guide to the use of statistical methods for obtaining reliable and practical survey research Applied Survey Methods provides a comprehensive outline of the complete survey process, from design to publication. Filling a gap in the current literature, this one-of-a-kind book describes both the theory and practical applications of survey research with an emphasis on the statistical aspects of survey methods. The book begins with a brief historic overview of survey research methods followed by a discussion that details the needed first steps for carrying out a survey, including the definition of a target population, the selection of a sampling frame, and the outline of a questionnaire with several examples that include common errors to avoid in the wording of questions. Throughout the book, the author provides an accessible discussion on the methodological problems that are associated with the survey process, outlining real data and examples while also providing insight on the future of survey research. Chapter coverage explores the various aspects of the survey process and the accompanying numerical techniques, including: Simple and composite sampling designs Estimators Data collection and editing The quality of results The non-response problem Weighting adjustments and methods Disclosure control The final chapter addresses the growing popularity of Web surveys, and the associated methodological problems are discussed, including solutions to common pitfalls. Exercises are provided throughout with selected answers included at the end of the book, while a related Web site features additional solutions to exercises and a downloadable demo version of the Blaise system of computer-assisted interviewing. Access to the freely available SimSam software is also available on the related Web site and provides readers with the tools needed to simulate samples from finite populations as well as visualize the effects of sample size, non-response, and the use of different estimation procedures. Applied Survey Methods is an excellent book for courses on survey research and non-response in surveys at the upper-undergraduate and graduate levels. It is also a useful reference for practicing statisticians and survey methodologists who work in both government and private research sectors.

Theory Based Data Analysis For The Social Sciences

Author: Carol S. Aneshensel
Editor: SAGE
ISBN: 1412994357
Size: 13,35 MB
Format: PDF
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This book presents a method for bringing data analysis and statistical technique into line with theory. The author begins by describing the elaboration model for analyzing the empirical association between variables. She then introduces a new concept into this model, the focal relationship. Building upon the focal relationship as the cornerstone for all subsequent analysis, two analytic strategies are developed to establish its internal validity: an exclusionary strategy to eliminate alternative explanations, and an inclusive strategy which looks at the interconnected set of relationships predicted by theory. Using real examples of social research, the author demonstrates the use of this approach for two common forms of analysis, multiple linear regression and logistic regression. Whether learning data analysis for the first time or adding new techniques to your repertoire, this book provides an excellent basis for theory-based data analysis.

Applied Panel Data Analysis For Economic And Social Surveys

Author: Hans-Jürgen Andreß
Editor: Springer Science & Business Media
ISBN: 3642329144
Size: 15,60 MB
Format: PDF, ePub, Mobi
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Many economic and social surveys are designed as panel studies, which provide important data for describing social changes and testing causal relations between social phenomena. This textbook shows how to manage, describe, and model these kinds of data. It presents models for continuous and categorical dependent variables, focusing either on the level of these variables at different points in time or on their change over time. It covers fixed and random effects models, models for change scores and event history models. All statistical methods are explained in an application-centered style using research examples from scholarly journals, which can be replicated by the reader through data provided on the accompanying website. As all models are compared to each other, it provides valuable assistance with choosing the right model in applied research. The textbook is directed at master and doctoral students as well as applied researchers in the social sciences, psychology, business administration and economics. Readers should be familiar with linear regression and have a good understanding of ordinary least squares estimation. ​

Market Data Analysis Using Jmp Hardcover Edition

Author: Walter R. Paczkowski
Editor: SAS Institute
ISBN: 1629604852
Size: 11,94 MB
Format: PDF, Docs
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With the powerful interactive and visual functionality of JMP, you can dynamically analyze market data to transform it into actionable and useful information with clear, concise, and insightful reports and displays. Market Data Analysis Using JMP is a unique example-driven book because it has a specific application focus: market data analysis. A working knowledge of JMP will help you turn your market data into vital knowledge that will help you succeed in a highly competitive, fast-moving, and dynamic business world. This book can be used as a stand-alone resource for working professionals, or as a supplement to a business school course in market data research. Anyone who works with market data will benefit from reading and studying this book, then using JMP to apply the dynamic analytical concepts to their market data. After reading this book, you will be able to quickly and effortlessly use JMP to: prepare market data for analysis use and interpret sophisticated statistical methods build choice models estimate regression models to turn data into useful and actionable information Market Data Analysis Using JMP will teach you how to use dynamic graphics to illustrate your market data analysis and explore the vast possibilities that your data can offer!

Handbook Of Health Survey Methods

Author: Timothy P. Johnson
Editor: John Wiley & Sons
ISBN: 1118594746
Size: 18,17 MB
Format: PDF, ePub, Mobi
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A comprehensive guidebook to the current methodologiesand practices used in health surveys A unique and self-contained resource, Handbook of HealthSurvey Methods presents techniques necessary for confrontingchallenges that are specific to health survey research. Thehandbook guides readers through the development of sample designs,data collection procedures, and analytic methods for studies aimedat gathering health information on general and targetedpopulations. The book is organized into five well-defined sections: Design andSampling Issues, Measurement Issues, Field Issues, Health Surveysof Special Populations, and Data Management and Analysis.Maintaining an easy-to-follow format, each chapter begins with anintroduction, followed by an overview of the main concepts,theories, and applications associated with each topic. Finally,each chapter provides connections to relevant online resources foradditional study and reference. The Handbook of Health SurveyMethods features: 29 methodological chapters written by highly qualified expertsin academia, research, and industry A treatment of the best statistical practices and specificmethodologies for collecting data from special populations such assexual minorities, persons with disabilities, patients, andpractitioners Discussions on issues specific to health research includingdeveloping physical health and mental health measures, collectinginformation on sensitive topics, sampling for clinical trials,collecting biospecimens, working with proxy respondents, andlinking health data to administrative and other external datasources Numerous real-world examples from the latest research in thefields of public health, biomedicine, and health psychology Handbook of Health Survey Methods is an ideal reference foracademics, researchers, and practitioners who apply survey methodsand analyze data in the fields of biomedicine, public health,epidemiology, and biostatistics. The handbook is also a usefulsupplement for upper-undergraduate and graduate-level courses onsurvey methodology.

Linear Mixed Models

Author: Brady T. West
Editor: CRC Press
ISBN: 1466561025
Size: 11,94 MB
Format: PDF, Docs
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Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues to lead readers step by step through the process of

Multiple Imputation Of Missing Data Using Sas

Author: Patricia Berglund
Editor: SAS Institute
ISBN: 162959203X
Size: 19,48 MB
Format: PDF, Mobi
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Find guidance on using SAS for multiple imputation and solving common missing data issues. Multiple Imputation of Missing Data Using SAS provides both theoretical background and constructive solutions for those working with incomplete data sets in an engaging example-driven format. It offers practical instruction on the use of SAS for multiple imputation and provides numerous examples that use a variety of public release data sets with applications to survey data. Written for users with an intermediate background in SAS programming and statistics, this book is an excellent resource for anyone seeking guidance on multiple imputation. The authors cover the MI and MIANALYZE procedures in detail, along with other procedures used for analysis of complete data sets. They guide analysts through the multiple imputation process, including evaluation of missing data patterns, choice of an imputation method, execution of the process, and interpretation of results. Topics discussed include how to deal with missing data problems in a statistically appropriate manner, how to intelligently select an imputation method, how to incorporate the uncertainty introduced by the imputation process, and how to incorporate the complex sample design (if appropriate) through use of the SAS SURVEY procedures. Discover the theoretical background and see extensive applications of the multiple imputation process in action. This book is part of the SAS Press program.