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.

Nonsampling Error in Sample Surveys

Whatever the mode of data collection used involving a survey, the researcher needs to be aware that any process of asking questions and soliciting answers from people involves a complex set of tasks, and that the process itself—as well as the instrument design—engenders nonsampling error and bias that affect the validity and reliability of the data generated through the survey process.

D. Amedeo, R. K. Golledge, & R. J. Simpson, 2009, p. 107

The use of sample surveys to collect important data in the social and decision sciences faces a number of important, interrelated challenges. Among these are fewer people are willing to participate in all kinds of social surveys; citizens in most industrialized nations report alarmingly low levels of trust in ...

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