Summary
Contents
Subject index
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.
Interviewer Error
Interviewer Error
The conscientious [survey] researcher cannot assume an ostrich-like posture and make believe that interviewing errors are small, under control, and hence not worthy of attention. Interviewing errors may be large and are related to interviewing quality. As long as interviewing quality remains an overlooked ingredient in [survey] research, the results obtained are likely to be faulty and hence may be misleading.
As of the date of this note by Mayer, interviewer error was a problem that survey planners had already been dealing with for a long time. The problem still exists. And, although computer-assisted data-gathering methods and paid professional interviewing organizations may have lowered the interviewer error rate somewhat, field experience and current American Statistical Association conference paper topics ...
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