Linda B. Bourque - Böcker
1 265 kr
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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." --Peter Hernon, Graduate School of Library and Information Science, Simmons College
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.
1 178 kr
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"The writing style is good, clear, and accurate, with a logical presentation of material. The checklists are effective learning aids." --Carol J. Lancaster, Medical University of South Carolina
When should you use a telephone survey, and how do you transform completed telephone interviews into an analyzable, machine-readable data file? This book shows readers how to develop and administer telephone surveys (with particular attention to paper-and-pencil administration) and prepare the results for analysis. Using detailed examples and checklists, the authors explain the different kinds of telephone surveys, how to determine which telephone data collection method to use, and how to design and administer the questionnaires. Information is included for adapting questions originally designed for use in self-administered questionnaires or other data collection modalities. Language issues are discussed, including literacy and language level usage, and basic steps for translating survey materials into other languages.
The authors also offer tips for:
Interacting with and motivating respondents Handling "call backs" and "refusal conversions" Selecting, training, and supervising interviewers Sampling, with particular attention to random digit dialing (RDD) procedures Calculating response ratesProcessing Data
The Survey Example
804 kr
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"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.