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Introduction to Survey Sampling

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
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


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


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


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

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

For instructors

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