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.

Measurement Error

Measurement errors can have severe biasing effects on the estimation and data analysis and will often reduce the precision of the estimates and power of statistical tests. The evaluation of measurement errors in US surveys has become an important goal of national statistical agencies … as well as non-Government survey research organizations.

Paul P. Biemer and Christopher Wiesen, 2002, p. 97

The quality of all surveys depends in large part upon the ability of the researchers to collect accurate data. It is dependent upon how well or poorly a survey instrument is designed and the way the sample data collected actually represent the desired measurements of a specified population. Measurement error can occur regardless of the type of instrument or approach used—including self-administered questionnaires; diaries; ...

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