Enhance the quality of survey results by recognizing and
reducing measurement errors.
Margins of Error: A Study of Reliability in Survey Measurement
demonstrates how and hwy identifying the presence and extent of
measurement errors in survey data is essential for improving the
overall collection and analysis of the data. The author outlines
the consequences of ignoring survey measurement errors and also
discusses ways to detect and estimate the impact of these errors.
This book also provides recommendations of improving the quality of
survey data.
Logically organized and clearly written, this book:
* Deconstructs the data gathering process into six main elements
of the response process: question adequacy, comprehension,
accessibility, retrieval, motivation, and communication
* Provides an exhaustive review of valuable reliability
estimation techniques that can be applied to survey data
* Identifies the types of questions and interviewer practices
that are essential to the collection of reliable data
* Addresses hypotheses regarding which survey questions, sources
of information, and questionnaire formats produce the most reliable
data
In conjunction with research data gathered on nearly 500 survey
measures and the application of an empirical approach grounded in
classical measurement theory, this book discusses the sources of
measurement error and provides the tools necessary for improving
survey data collection methods.
Margins of Error enables statisticians and researchers in the
fields of public opinion and survey research to design studies that
can detect, estimate, and reduce measurement errors that may have
previously gone undetected. This book also serves as a supplemental
textbook for both undergraduate and graduate survey methodology
courses.
Table des matières
Preface.
Acknowledgements.
Foreward.
1. Measurement Errors in Surveys.
2. Sources of Survey Measurement Error.
3. Reliability Theory for Survey Measures.
4. Reliability Methods for Multiple Measures.
5. Longitudinal Methods for Reliability Estimation.
6. Using Longitudinal Data to Estimate Reliability
Parameters.
7. The Source and Content of Survey Questions.
8. Survey Question Context.
9. Formal Properties of Survey Questions.
10. Attributes of Respondents.
11. Reliability Estimation for Categorical Latent Variables.
12. Final Thoughts and Future Directions.
Appendix.
References.
Index.
A propos de l’auteur
Duane F. Alwin, PHD, is Mc Courtney Professor of Sociology and Demography and Director of the Center on Population Health and Aging at Pennsylvania State University. In addition to a concentration on survey methodology, his research interests include a wide range of phenomena concerned with the connection of human development and social change, as well as the impact of demographic and historical processes on individual cognitive, ideological, and attitudinal development. Dr. Alwin has published extensively in social science literature and is the recipient of more than two dozen prestigious awards, grants, and special university honors.