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"The authors discuss self-administered questionnaires, the content and format of the questionnaire, "user-friendly" questionnaires and response categories, and survey implementation. They offer excellent checklists for deciding whether or not to use a mail questionnaire, for constructing questions and response categories, for minimizing bias, for writing questionnaire specifications, for formatting and finalizing questionnaires, and for motivating respondents and writing cover letters."
How do you decide whether a self-administered questionnaire is appropriate for your research question? This book provides readers with an answer to this question while giving them all the basic tools needed for conducting a self-administered or mail survey. Updated to include data from the 2000 Census, the authors show how to develop questions and format a user-friendly questionnaire; pretest, pilot test, and revise questionnaires; and write advance and cover letters that help motivate and increase response rates. They describe how to track and time follow-ups to non-respondents; estimate personnel requirements; and determine the costs of a self-administered or mailed survey. They also demonstrate how to process, edit, and code questionnaires; keep records; fully document how the questionnaire was developed and administered; and how the data collected is related to the questionnaire. New to this edition is expanded coverage on Web-based questionnaires, and literacy and language issues.
"Clear and concise in its recommendations, this book should find its place on lists of required reading for all practical survey design and analysis courses." --The Statistician Although data processing is frequently thought to occur only after the data are collected, it actually occurs throughout the phase of study design, implementation, and analysis. Decisions made during the design of data collection instrument influence the kind of data and the format of the data available for analysis. Devoted entirely to data processing, this much needed volume addresses such key issues as: Should you create your own instrument for a questionnaire? How do you test a questionnaire? What are the characteristics of good data processing? How do you deal with missing data? How do you scale an evaluation and create subfiles for analysis? Processing Data begins with a discussion on the selection of the data selection techniques and how this impacts data processing and the data for later analysis. Each major section concludes with examples, and when appropriate, directs the reader to commonly available computer software that can aid in data processing.
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