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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Dr. David E. McNabb is a Professor Emeritus and an adjunct professor at the Pacific Lutheran University School of Business. He has taught undergraduate and graduate business courses for the University of Maryland–University College in Europe, the American University in Bulgaria, the Stockholm School of Economics in Riga, Latvia, and a regional business education program in Northern France. He has also taught for several years for the MPA program at Evergreen State College, the Oregon State University, the University of Washington–Tacoma, and Olympic College. He served as a member of a consulting team investigating nonsampling error remediation for the US Census Bureau. The first edition of his book Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches received the Grenzebach Prize for Outstanding Published Scholarship in Philanthropy.
This text looks at what many survey scientists believe to be the largest source of error: nonsampling error.
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