• Step-by-step instructions for calculating survey weights
  • Extensive real-world examples and applications throughout
  • Demonstrates how to use existing software to solve survey problems
  • The most up-to-date textbook and professional reference for statistical survey sampling



Autorentext

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.



Klappentext

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.



Inhalt

Preface
Acknowledgements
1 An Overview of Sample Design and Weighting
1.1 Background and Terminology
1.2 Chapter Guide
Part I Designing Single-Stage Sample Surveys
2 Project 1: Design a Single-Stage Personnel Survey
2.1 Specifications for the Study
2.2 Questions Posed by the Design Team
2.3 Preliminary Analyses
2.4 Documentation
2.5 Next Steps
3 Sample Design and Sample Size for Single-Stage Surveys
3.1 Determining a Sample Size for a Single-Stage Design
3.1.1 Simple Random Sampling
3.1.2 Stratified Simple Random Sampling
3.2 Finding Sample Sizes When Sampling with Varying Probabilities
3.2.1 Probability Proportional to Size Sampling
3.2.2 Regression Estimates of Totals
3.3 Other Methods of Sampling
3.4 Estimating Population Parameters from a Sample
3.5 Special Topics
3.5.1 Rare Characteristics
3.5.2 Domain Estimates
3.6 More Discussion of Design Effects
3.7 Software for Sample Selection
3.7.1 R Packages
3.7.2 SAS PROC SURVEYSELECT
Exercises
4 Power Calculations and Sample Size Determination
4.1 Terminology and One-Sample Tests
4.2 Power in a One-Sample Test
4.3 Two-Sample Tests
4.3.1 Differences in Means
4.3.2 Differences in Proportions
4.3.3 Special Case: Relative Risk
4.3.4 Special Case: Effect Sizes
4.4 R Power Functions
4.5 Power and Sample Size Calculations in SAS.
Exercises
5 Mathematical Programming
5.1 Multicriteria Optimization
5.2 Microsoft Excel Solver
5.3 SAS PROC NLP
5.4 SAS PROC OPTMODEL
5.5 R Alabama Package
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6 Outcome Rates and Effect on Sample Size
6.1 Disposition Codes
6.2 Definitions of Outcome Rates
6.3 Sample Units with Unknown AAPOR Classification
6.4 Weighted Versus Unweighted Rates
6.5 Accounting for Sample Losses in Determining Initial Sample Size
Titel
Practical Tools for Designing and Weighting Survey Samples
EAN
9783319936321
Format
E-Book (pdf)
Veröffentlichung
12.10.2018
Digitaler Kopierschutz
Wasserzeichen
Dateigrösse
10.32 MB
Anzahl Seiten
776