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Nonsampling Error in Social Surveys

Autor David E. McNabb
en Limba Engleză Paperback – 16 sep 2013
A welcome and much-needed addition to the literature on survey data quality in social research, Nonsampling Error in Social Surveys, by David E. McNabb, examines the most common sources of nonsampling error: frame error; measurement error; response error, nonresponse error, and interviewer error. Offering the only comprehensive and non-technical treatment available, the book's focus on controlling error shows readers how to eliminate the opportunity for error to occur, and features revealing examples of past and current efforts to control the incidence and effects of nonsampling error. Most importantly, it gives readers the tools they need to understand, identify, address, and prevent the most prevalent and difficult-to-control types of survey errors.
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Specificații

ISBN-13: 9781452257426
ISBN-10: 1452257426
Pagini: 272
Dimensiuni: 152 x 229 x 15 mm
Greutate: 0.36 kg
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications, Inc
Locul publicării:Thousand Oaks, United States

Recenzii

“Provides the best non-technical introduction to the nonsampling errors I have ever read.”
“My doctoral students came from a variety of backgrounds. Most of them have little to zero survey research background. The book will serve to ignite class discussion and move it to the highest level.”

Cuprins

Preface
About the Author
Table of Contents
PART I: CONCEPTS AND ISSUES IN NONSAMPLING ERROR RESEARCH
1. Issues in Data Quality and Survey Ethics
2. Nonsampling Error in Sample Surveys
3. The Total Survey Error Paradigm
PART II: MAJOR SOURCES OF NONSAMPLING ERROR IN SURVEYS
4. Defining and Detecting Nonsampling Error in Sample Surveys
5. Frame Error
6. Measurement Error
7. Response Error
8. Nonresponse Error
9. Interviewer Error
PART III: ERROR CONTROL APPLICATIONS
10. Tools for Identifying Nonsampling Error in Survey Data
APPENDICES
Appendix A: Glossary
Appendix B: Standards and Guidelines for Statistical Surveys
Appendix C: Deming’s 14-Points for Quality
REFERENCES

Notă biografică


Descriere

This text looks at what many survey scientists believe to be the largest source of error: nonsampling error.