Total Survey Error in Practice

Preface

Total survey error (TSE) refers to the accumulation of all errors that may arise in the design, collection, processing, and analysis of survey data. In this context, a survey error can be defined as any error contributing to the deviation of an estimate from its true parameter value. Survey errors arise from misspecification of concepts, sample frame deficiencies, sampling, questionnaire design, mode of administration, interviewers, respondents, data capture, missing data, coding, and editing. Each of these error sources can diminish the accuracy of inferences derived from the survey data. A survey estimate will be more accurate when bias and variance are minimized, which occurs only if the influence of TSE on the estimate is also minimized. In addition, if major error sources are not taken into account, various measures of margins of error are understated, which is a major problem for the survey industry and the users of survey data.

Because survey data underlie many public policy and business decisions, a thorough understanding of the effects of TSE on data quality is needed. The TSE framework, the focus of this book, is a valuable tool for understanding and improving survey data quality. The TSE approach summarizes the ways in which a survey estimate may deviate from the corresponding parameter value. Sampling error, measurement error, and nonresponse error are the most recognized sources of survey error, but the TSE framework also encourages researchers not to ...