Extract: Multiple-frame surveys are susceptible to errors that stem from associating the over-lapping portions of the frames. Decreasing sampling error may improve precision, but it offers greater complications; nonsampling error would increase, leading to decreased accuracy and, perhaps, greater total error. This manuscript offers several procedures to improve consistency and accuracy of multiple-frame estimating by reducing nonsampling errors. Such procedures, when added to an optimum mix of sampling frames, would provide survey indications of greater reliability without increasing costs appreciably.

Extract: Multiple-frame surveys are susceptible to errors that stem from associating the over-lapping portions of the frames. Decreasing sampling error may improve precision, but it offers greater complications; nonsampling error would increase, leading to decreased accuracy and, perhaps, greater total error. This manuscript offers several procedures to improve consistency and accuracy of multiple-frame estimating by reducing nonsampling errors. Such procedures, when added to an optimum mix of sampling frames, would provide survey indications of greater reliability without increasing costs appreciably.

Extract: Multiple-frame surveys are susceptible to errors that stem from associating the over-lapping portions of the frames. Decreasing sampling error may improve precision, but it offers greater complications; nonsampling error would increase, leading to decreased accuracy and, perhaps, greater total error. This manuscript offers several procedures to improve consistency and accuracy of multiple-frame estimating by reducing nonsampling errors. Such procedures, when added to an optimum mix of sampling frames, would provide survey indications of greater reliability without increasing costs appreciably.

Excerpt from Error Profile for Multiple-Frame Surveys This report will show that there are several sources of nonsampling error in these surveys. These sources include failure to associate properly reporting unit and sampling unit, and failure to communicate clearly and concisely via the questionnaire, domain determination, estimation, and nonresponse. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

Statistical Methods and the Improvement of Data Quality contains the proceedings of The Small Conference on the Improvement of the Quality of Data Collected by Data Collection Systems, held on November 11-12, 1982, in Oak Ridge, Tennessee. The conference provided a forum for discussing the use of statistical methods to improve data quality, with emphasis on the problems of data collection systems and how to handle them using state-of-the-art techniques. Comprised of 16 chapters, this volume begins with an overview of some of the limitations of surveys, followed by an annotated bibliography on frames from which the probability sample is selected. The reader is then introduced to sample designs and methods for collecting data over space and time; response effects to behavior and attitude questions; and how to develop and use error profiles. Subsequent chapters focus on principles and methods for handling outliers in data sets; influence functions, outlier detection, and data editing; and application of pattern recognition techniques to data analysis. The use of exploratory data analysis as an aid in modeling and statistical forecasting is also described. This monograph is likely to be of primary benefit to students taking a general course in survey sampling techniques, and to individuals and groups who deal with large data collection systems and are constantly seeking ways to improve the overall quality of their data.

The development of a field or an area of inquiry is often marked by changes in measurement techniques, shifts in analytic emphasis, and disputes over the best ways of doing research. In many areas of psychology, a number of issues have characterized methodological evolution of the discipline, including questions regarding context and reductionism, or laboratory versus field research. For some of the newer areas in psychology, such as environment or health psychology, this is not an issue of either/or. Although there has been some debate about these trade-offs, it is generally regarded by people in this field that some combination of the two approaches is essential. Depending on the question being studied this balance may change. However, the questions asked are less likely to inquire ‘which way is better’ and concentrate on how both may be used. This observation serves to illustrate the fact that different research endeavours have different methodological issues. Originally published in 1985, this volume explores some of the issues characterizing work on health, environment, and behavior.