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.

Issues in Data Quality and Survey Ethics

[Survey] quality is difficult to define, but what is immediately apparent is that quality is multi-dimensional, is perceived in different ways, and is intimately linked to the way the end product is used. The quality of survey data is … built in (or destroyed) at various interlocking steps in the production of the data. Just as one can visualize the assembly-line production of manufactured goods, so one can visualize the assembly-line production of survey data. We might think of it in terms of the discrete stages of design, collection, processing, and interpretation. Poor quality at any one of these stages is carried through to the final end product.

Barbara A. Bailar, 1984, p. 43

This book is about identifying and ...

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