Margins of Error: A Study of Reliability in Survey Measurement
John Wiley & Sons, 2007. gada 9. jūl. - 416 lappuses
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:
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.
1.5. rezultāts no 36.
Specifically, is factual information gathered more precisely than attitudinal and/or other subjective data? Also, do types of nonfactual questions (attitudes, beliefs and self-assessments) differ in reliability?
In the case of factual data, are proxy reports as reliable as self-reports? How reliable are interviewer observations? ' Is reliability of measurement affected by the context in which the questions are framed?
We often assume that respondents have relatively easy access and can retrieve relatively recent factual material in their own lives. Since most people are employed and in the labor force, we might often assume that they can easily ...
Even though survey researchers often assume that self reports of factual information can be measured quite well, the fact is that even such hard variables as income and earnings are not perfectly measured.
All of these factors play a role in affecting the quality of survey data, whether the question seeks information of a factual nature, or whether it asks for reports of subjective states, such as beliefs and attitudes, ...