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This book addresses the needs of researchers who want to conduct surveys online. Issues discussed include sampling from online populations, developing online and mobile questionnaires, and administering electronic surveys, are unique to digital surveys. Others, like creating reliable and valid survey questions, data analysis strategies, and writing the survey report, are common to all survey environments. This single resource captures the particulars of conducting digital surveys from start to finish
The Survey of Income and Program Participation (SIPP) is a national, longitudinal household survey conducted by the Census Bureau. SIPP serves as a tool to evaluate the effectiveness of government-sponsored social programs and to analyze the impacts of actual or proposed modifications to those programs. SIPP was designed to fill a need for data that would give policy makers and researchers a much better grasp of how effectively government programs were reaching their target populations, how participation in different programs overlapped, and to what extent and under what circumstances people transitioned into and out of these programs. SIPP was also designed to answer questions about the short-term dynamics of employment, living arrangements, and economic well-being. The Census Bureau has reengineered SIPPâ€"fielding the initial redesigned survey in 2014. This report evaluates the new design compared with the old design. It compares key estimates across the two designs, evaluates the content of the redesigned SIPP and the impact of the new design on respondent burden, and considers content changes for future improvement of SIPP.
In this first book of the series Survey Methods in Educational Research, we have brought together leading authors and scholars in the field to discuss key introductory concepts in the creation, implementation, evaluation and dissemination of survey instruments and their resultant findings. While there are other textbooks that might introduce these concepts adequately well, the authors here have focused on the pragmatic issues that inevitably arise in the development and administration process of survey instruments. Drawing from their rich experiences, the authors present these potential speed bumps or road blocks a survey researcher in education or the social sciences might encounter. Referencing their own work and practice, the authors provide valuable suggestions for dealing with these issues “your advisor never told you about.” And all of the recommendations are aligned with standard protocols and current research on best practices in the field of research methodology. This book is broken into four broad units on creating survey items and instruments, administering surveys, analyzing the data from surveys, and stories of successful administrations modeling the entire research cycle. Each chapter focuses on a different concept in the survey research process, and the authors share their approaches to addressing the issues. These topics include survey item construction, scale development, cognitive interviewing, measuring change with self-report data, translation issues with surveys administered in multiple languages, working with school and program administrators when implementing surveys, a review of current software used in survey research, the use of weights, response styles, assessing validity of results, and effectively communicating your results and findings … and much more. The intended audience of the volume will be practitioners, administrators, teachers as researchers, graduate students, social science and education researchers not experienced in survey research, and students learning program evaluation. In brief, if you are considering doing survey research, this book is meant for you.
These Guidelines represent the first attempt to provide international recommendations on collecting, publishing, and analysing subjective well-being data.
Synthesizing the literature from the survey and measurement fields, this book explains how to develop closed-response survey scales that will accurately capture such constructs as attitudes, beliefs, or behaviors. It provides guidelines to help applied researchers or graduate students review existing scales for possible adoption or adaptation in a study; create their own conceptual framework for a scale; write checklists, true-false variations, and Likert-style items; design response scales; examine validity and reliability; conduct a factor analysis; and document the instrument development and its technical quality. Advice is given on constructing tables and graphs to report survey scale results. Concepts and procedures are illustrated with "Not This/But This" examples from multiple disciplines. User-Friendly Features *End-of-chapter exercises with sample solutions, plus annotated suggestions for further reading. *"Not This/But This" examples of poorly written and strong survey items. *Chapter-opening overviews and within-chapter summaries. *Glossary of key concepts. *Appendix with examples of parametric and nonparametric procedures for group comparisons.
This book presents contemporary empirical methods in software engineering related to the plurality of research methodologies, human factors, data collection and processing, aggregation and synthesis of evidence, and impact of software engineering research. The individual chapters discuss methods that impact the current evolution of empirical software engineering and form the backbone of future research. Following an introductory chapter that outlines the background of and developments in empirical software engineering over the last 50 years and provides an overview of the subsequent contributions, the remainder of the book is divided into four parts: Study Strategies (including e.g. guidelines for surveys or design science); Data Collection, Production, and Analysis (highlighting approaches from e.g. data science, biometric measurement, and simulation-based studies); Knowledge Acquisition and Aggregation (highlighting literature research, threats to validity, and evidence aggregation); and Knowledge Transfer (discussing open science and knowledge transfer with industry). Empirical methods like experimentation have become a powerful means of advancing the field of software engineering by providing scientific evidence on software development, operation, and maintenance, but also by supporting practitioners in their decision-making and learning processes. Thus the book is equally suitable for academics aiming to expand the field and for industrial researchers and practitioners looking for novel ways to check the validity of their assumptions and experiences. Chapter 17 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
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