A welcome and much-needed addition to the literature on survey data quality in social research, McNabb's book 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.

The Total Survey Error Paradigm

The total survey error paradigm is the conceptual foundation of the field of survey methodology. Its roots lie in cautions by the founders of sample surveys that the quality properties of survey statistics are functions of essential survey conditions that are independent of the sample design. … The strengths of [TSE] are the explicit attention to the decomposition of errors, the separation of phenomena affecting statistics in various ways, and its success in forming the basis of the field of survey methodology, pointing the direction for new research.

R. M. Groves and L. Lyberg, 2010, pp. 874–875

This introductory statement by survey researchers Groves and Lyberg reinforces the recognition by survey producers and users that increasing difficulties in gaining respondent participation and ...

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