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.
Defining and Classifying Nonsampling Error
Defining and Classifying Nonsampling Error
The reliability of a survey is a function of its total survey error, which is composed of two components: random sampling error and nonsampling error. … The consistent finding is that nonsampling error is the major contributor to total survey error, while random sampling error is minimal.
The use of surveys to collect information is a popular research method in all of the social sciences. Researchers use surveys to collect data on such diverse topics as the behavior, thoughts, actions, and values of individuals, family units, social groups, and membership of organizations. Others use surveys to describe the characteristics of populations, samples, and subsamples; to explain behavioral phenomena; and to explain how variables are ...
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