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This is the first e-book that presents some insights into the construction of Mokken scales with complex survey data, and, in particular, the estimation of Mokken's scalability coefficients - Hij, Hi, and H - with binary responses. Every day, researchers work with complex samples selected from finite populations of interest to make inferences about population parameters. However, in many situations these samples are assumed as SRS samples. Serious consequences have been reported in the complex survey data literature; when this assumption is considered. I invite you to find out a little more about some relevant contributions to the development of the Psychometry under complex sampling designs, as highlighted in this e-book. Keywords: Mokken scaling, Mokken scale analysis, complex data, Complex Mokken, design effect, clustering, sampling weights, stratification, clustered samples, variance estimation, point estimation, large-scale educational surveys, Jackknife resampling technique, Non Parametric Item Response Theory.
For social researchers who need to know what procedures to use under what circumstances in practical research projects, this book does not require an indepth understanding of statistical theory.
This second edition has been revised and updated to reflect key methodological developments in health research. It is a comprehensive, easy to read, guide to the range of methods used to study and evaluate health and health services. It describes the concepts and methods used by the main disciplines involved in health research, including: demography, epidemiology, health economics, psychology and sociology.
This volume introdudes social science students and researchers to the theory and practice of the highly powerful methods of nonpatametric item response theory (IRT).
A new edition of this practical guide for clinicians who are developing tools to measure subjective states, attitudes, or non-tangible outcomes in their patients, suitable for those who have no knowledge of statistics.
This is an immensely helpful book for students starting their own research... an excellent introduction to the comparative method giving an authoritative overview over the research process - Klaus Armingeon, University of Bern Doing Research in Political Science is the book for mastering the comparative method in all the social sciences - Jan-Erik Lane, University of Geneva This book has established itself as a concise and well-readable text on comparative methods and statistics in political science I...strongly recommend it. - Dirk Berg-Schlosser, Philipps-University Marburg This thoroughly revised edition of the popular textbook offers an accessible but comprehensive introduction to comparative research methods and statistics for students of political science. Clearly organized around three parts, the text introduces the main theories and methodologies used in the discipline. Part 1 frames the comparative approach within the methodological framework of the political and social sciences. Part 2 introduces basic descriptive and inferential statistical methods as well as more advanced multivariate methods used in quantitative political analysis. Part 3 applies the methods and techniques of Parts 1 & 2 to research questions drawn from contemporary themes and issues in political science. Incorporating practice exercises, ideas for further reading and summary questions throughout, Doing Research in Political Science provides an invaluable step-by-step guide for students and researchers in political science, comparative politics and empirical political analysis.
The work provides general guidance about questionnaire design, development, and pre-testing sequence, with an emphasis on the cognitive interview.
This book aims to explain the basics of graph theory that are needed at an introductory level for students in computer or information sciences. To motivate students and to show that even these basic notions can be extremely useful, the book also aims to provide an introduction to the modern field of network science. Mathematics is often unnecessarily difficult for students, at times even intimidating. For this reason, explicit attention is paid in the first chapters to mathematical notations and proof techniques, emphasizing that the notations form the biggest obstacle, not the mathematical concepts themselves. This approach allows to gradually prepare students for using tools that are necessary to put graph theory to work: complex networks. In the second part of the book the student learns about random networks, small worlds, the structure of the Internet and the Web, peer-to-peer systems, and social networks. Again, everything is discussed at an elementary level, but such that in the end students indeed have the feeling that they: 1.Have learned how to read and understand the basic mathematics related to graph theory. 2.Understand how basic graph theory can be applied to optimization problems such as routing in communication networks. 3.Know a bit more about this sometimes mystical field of small worlds and random networks. There is an accompanying web site www.distributed-systems.net/gtcn from where supplementary material can be obtained, including exercises, Mathematica notebooks, data for analyzing graphs, and generators for various complex networks.
For many readers, data theory is probably unfamiliar. Data isn't usually the subject matter of theory in and of itself. However, in this volume, William Jacoby introduces a theory of data idea. It examines how real world observations are transformed into something to be analyzed that is, data. Jacoby explores some of the basic ideas of data theory, and considers their implications for research strategies in the social sciences. "Like others in the series, it is reassuringly slim. It is intended for a general social science readership and is a worthwhile read even for experienced data analysts. since it draws attention not only to often overlooked assumptions, but also to often ignored analysis possibilities." --Telephone Surveys "On the whole, this book contains a lot of useful information." --Journal of Classification
The invited authors of this edited volume have been prolific in the arena of Real Data Analysis (RDA) as it applies to the social and behavioral sciences, especially in the disciplines of education and psychology. Combined, this brain trust represents 3,247 articles in refereed journals, 127 books published, US $45.3 Million in extramural research funding, 34 teaching and 92 research awards, serve(d) as Editor/Assistant Editor/Editorial Board Member for 95 peer reviewed journals, and provide (d) ad hoc reviews for 362 journals. Their enormous footprint on real data analysis is showcased for professors, researchers, educators, administrators, and graduate students in the second text in the AERA/SIG ES Quantitative Methods series.