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Sample design is key to all surveys, fundamental to data collection, and to the analysis and interpretation of the data. Introduction to Survey Sampling, Second Edition provides an authoritative and accessible source on sample design strategies and procedures that is a required reading for anyone collecting or analyzing survey data. Graham Kalton discusses different types of probability samples, stratification (pre and post), clustering, dual frames, replicates, response, base weights, design effects, and effective sample size. It is a thorough revision and update of the first edition, published more than 35 years ago. Although the concepts of probability sampling are largely the same, there have been important developments in the application of these concepts as research questions have increasingly spanned multiple disciplines, computers have become central to data collection as well as data analysis, and cell phones have become ubiquitous, but response rates have fallen, and public willingness to engage in survey research has waned. While most of the volume focuses on probability samples, there is also a chapter on nonprobability samples, which are becoming increasingly important with the rise of social media and the world wide web.


 
Series Editor Introduction
 
Preface
 
Acknowledgments
 
About the Author
 
Chapter 1: Introduction to Survey Sampling
 
Chapter 2: Simple Random Sampling
 
Chapter 3: Systematic Sampling
 
Chapter 4: Stratification
Proportionate Stratification

 
Disproportionate Stratification

 
Choice of Strata

 
Poststratification

 
 
Chapter 5: Cluster and Multi-Stage Sampling
 
Chapter 6: Probability Proportional to Size Sampling
 
Chapter 7: Other Probability Designs
Two-Phase Sampling

 
Dual-Frame Sampling

 
Replicated Sampling

 
Designs for Surveys Over Time

 
Responsive and Adaptive Designs

 
 
Chapter 8: Sampling Frames
Missing Elements

 
Clusters

 
Blanks and Foreign Elements

 
Duplicate Listings

 
Unlocatable Listings

 
Address-Based Sampling

 
Sampling for Telephone Surveys

 
 
Chapter 9: Nonresponse
Unit Nonresponse

 
Item Nonresponse

 
 
Chapter 10: Base Weights
 
Chapter 11: Compensating for Missing Data
Nonresponse Weighting Adjustments

 
Calibration Adjustments

 
Imputation

 
 
Chapter 12: Variance Estimation
The Taylor Series Linearization Method

 
Balanced Repeated Replications

 
Jackknife Repeated Replications

 
The Bootstrap

 
Some General Issues

 
 
Chapter 13: Sample Size
 
Chapter 14: Examples of National Probability Sample Designs
National Household Surveys in Sub-Saharan Africa

 
The 2016 American National Election Study

 
The 2017 California Health Interview Survey

 
The American Community Survey

 
 
Chapter 15: Nonprobability Sampling
Quota Sampling

 
Sampling Methods for “Hard-to-Survey” Populations

 
Sampling Methods for Internet Surveys

 
Small-Area Estimation

 
 
Chapter 16: Concluding Remarks
 
References
 
Index

This book is a second revision of what will continue to be the classic short treatment of the subject.

Victor Ferreros
Walden University

“A wonderful resource for professionals who utilize survey sampling methodology. It provides indepth

information for readers on ways to improve survey schemes.” 

Joseph C. Kush, Ph.D.
Duquesne University

“This updated edition is a welcome addition to the field of survey sampling. Kalton provides a

concise and accessible approach to the design of complex sample surveys. New or expanded

topics address sampling challenges in an online world, issues of missing data, variance estimation

and adaptations of sampling methods for hard-to-reach populations. I’m looking forward to using

this 2nd edition in my sampling course!” 

Ann A. O’Connell, Ed.D.
The Ohio State University

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