Umfang:
Online-Ressource (XXI, 670 p. 64 illus, digital)
ISBN:
9781461464495
Serie:
Statistics for Social and Behavioral Sciences 51
Inhalt:
Designing Single-stage Sample Surveys -- Multistage Designs -- Survey Weights and Analyses -- Other Topics -- Appendices.
Inhalt:
Survey sampling is fundamentally an applied field. The goal in this book is to put an array of tools at the fingertips of practitioners 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 book serves at least three audiences: (1) Students seeking a more in-depth understanding of applied sampling either through a second semester-long course or by way of a supplementary reference; (2) Survey statisticians searching for practical guidance on how to apply concepts learned in theoretical or applied sampling courses; and (3) Social scientists and other survey practitioners who desire insight into the statistical thinking and steps taken to design, select, and weight random survey samples. Several survey data sets are used to illustrate how to design samples, to make estimates from complex surveys for use in optimizing the sample allocation, and to calculate weights. Realistic survey projects are used to demonstrate the challenges and provide a context for the solutions. The book covers several topics that either are not included or are dealt with in a limited way in other texts. These areas include: sample size computations for multistage designs; power calculations related to surveys; mathematical programming for sample allocation in a multi-criteria optimization setting; nuts and bolts of area probability sampling; multiphase designs; quality control of survey operations; and statistical software for survey sampling and estimation. An associated R package, PracTools, contains a number of specialized functions for sample size and other calculations. The data sets used in the book are also available in PracTools, so that the reader may replicate the examples or perform further analyses. Richard Valliant is a Research Professor at the Institute for Social Research of 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 is a Senior Research Statistician at RTI International in Washington, D.C. where she works on a variety of surveys related to health care and education. Her current research interests include software for optimizing complex sample designs, variance estimation using calibrated analysis weights, and methods to evaluate the utility of non-probability sampling. Frauke Kreuter is an Associate Professor in the Joint Program in Survey Methodology at the University of Maryland, USA; Professor of Statistics at Ludwig-Maximilians-Universität in Munich, Germany; and head of the Statistical Methods Research Department at the Institute for Employment Research (IAB) in Nürnberg, Germany. Currently she is associate editor of the Journal of the Royal Statistical Society, Journal of Official Statistics, Sociological Methods and Research, Survey Research Methods, and the Stata Journal.
Anmerkung:
Description based upon print version of record
,
Preface; Acknowledgments; Contents; List of Figures; Chapter1 An Overview of Sample Design and Weighting; 1.1 Background and Terminology; 1.2 Chapter Guide; Part I Designing Single-Stage Sample Surveys; Chapter2 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; Chapter3 Sample Design and Sample Size for Single-StageSurveys; 3.1 Determining a Sample Size for a Single-Stage Design; 3.1.1 Simple Random Sampling; 3.1.2 Stratified Simple Random Sampling
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3.2 Finding Sample Sizes When Sampling with Varying Probabilities3.2.1 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; Chapter4 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
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4.3.1 Differences in Means4.3.2 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; Chapter5 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; 5.6 Accounting for Problem Variations; Exercises; Chapter6 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
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6.4 Weighted Versus Unweighted Rates6.5 Accounting for Sample Losses in Determining Initial Sample Size; 6.5.1 Sample Size Inflation Rates at Work; 6.5.2 Replicates; Exercises; Chapter7 The Personnel Survey Design Project: One Solution; 7.1 Overview of the Project; 7.2 Formulate the Optimization Problem; 7.2.1 Objective Function; 7.2.2 Decision Variables; 7.2.3 Optimization Parameters; 7.2.4 Specified Survey Constraints; 7.3 One Solution; 7.3.1 Power Analyses; 7.3.2 Optimization Results; 7.4 Additional Sensitivity Analysis; 7.5 Conclusion; Part II Multistage Designs
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Chapter8 Project 2: Designing an Area SampleChapter9 Designing Multistage Samples; 9.1 Types of PSUs; 9.2 Basic Variance Results; 9.2.1 Two-Stage Sampling; 9.2.2 Nonlinear Estimators in Two-Stage Sampling; 9.2.3 More General Two-Stage Designs; 9.2.4 Three-Stage Sampling; 9.3 Cost Functions and Optimal Allocations for Multistage Sampling; 9.3.1 Two-Stage Sampling When Numbers of Sample PSUs and Elements per PSU Are Adjustable; 9.3.2 Three-Stage Sampling When Sample Sizes Are Adjustable; 9.3.3 Two- and Three-Stage Sampling with a Fixed Set of PSUs
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9.4 Estimating Measures of Homogeneity and Variance Components
Weitere Ausg.:
ISBN 9781461464488
Weitere Ausg.:
Erscheint auch als Druck-Ausgabe Valliant, Richard, 1950 - Practical tools for designing and weighting survey samples New York, NY : Springer, 2013 ISBN 9781461464488
Sprache:
Englisch
Fachgebiete:
Soziologie
Schlagwort(e):
Demoskopie
;
Empirische Sozialforschung
;
Methode
;
Demoskopie
;
Empirische Sozialforschung
;
Methode
DOI:
10.1007/978-1-4614-6449-5
URL:
Volltext
(lizenzpflichtig)
URL:
Volltext
(lizenzpflichtig)
Mehr zum Autor:
Kreuter, Frauke
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