The IRT chapter introduces the use of IRT models for evaluating a set of items designed to measure a specific trait such as an attitude, value, or a belief. Acock shows how to use the irt suite of commands, which are new in Stata 14, to fit IRT models and to graph the results. In addition, he presents a measure of reliability that can be computed when using IRT. After reading this introductory text, you will be able to enter, build, and manage a data set as well as perform fundamental statistical analyses.
New to the Third Edition A new chapter on the analysis of missing data and the use of multiple-imputation methods Extensive revision of the chapter on ANOVA Additional material on the application of power analysis The book covers data management; good work habits, including the use of basic do-files; basic exploratory statistics, including graphical displays; and analyses using the standard array of basic statistical tools, such as correlation, linear and logistic regression, and parametric and nonparametric tests of location and dispersion.
Rather than splitting these topics by their Stata implementation, the material on graphics and postestimation are woven into the text in a natural fashion. The author teaches Stata commands by using the menus and dialog boxes while still stressing the value of do-files. Each chapter includes exercises and real data sets are used throughout. This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis EFA using Stata.
In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots of Stata code and recommends evidence-based best practice procedures. This is an eminently applied, practical approach with few or no formulas and is aimed at readers with little to no mathematical background. Watkins maintains an accessible tone throughout and uses minimal jargon and formula to help facilitate grasp of the key issues users will face when applying EFA, along with how to implement, interpret, and report results.
Copious scholarly references and quotations are included to support the reader in responding to editorial reviews. This is a valuable resource for upper level undergraduate and postgraduate students, as well as for more experienced researchers undertaking multivariate or structure equation modeling courses across the behavioral, medical, and social sciences.
Best-selling, all-encompassing textbook for research methods in education. This book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets learners who would benefit from learning more conceptually and less computationally about statistical procedures and the software packages that can be used to implement them.
This book provides a comprehensive overview of this important research skill domain with an emphasis on visual support for learning and better understanding. The primary focus is on fundamental concepts, procedures and interpretations of statistical analyses within a single broad illustrative research context. The book covers a wide range of descriptive, correlational and inferential statistical procedures as well as more advanced procedures not typically covered in introductory and intermediate statistical texts.
It is an ideal reference for postgraduate students as well as for researchers seeking to broaden their conceptual exposure to what is possible in statistical analysis. Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work.
Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Combines statistics and operations research modeling to teach the principles of business analytics Written for students who want to apply statistics, optimization and multivariate modeling to gain competitive advantages in business Shows how powerful software packages, such as SPSS and Stata, can create graphical and numerical outputs.
Disasters and Economic Recovery provides perspectives on the economic issues that emerge before, during, and after natural disasters in an international context, by assessing the economic development patterns that emerge before and after disaster.
This book will provide a historical overview of emergency management policy and previous responses to disasters in each country, as well as the policy learning that occurred in each case leading up to the disasters under analysis.
Using time-series data, the book shows the emergence of new industries and job hiring patterns in the immediate aftermath, as well as provides a picture of the economic performance of each country in the years following each event. Looking at the economic development policies pre- and post-disaster, readers will glean important lessons on how to build resilient economies within the disaster framework, highlighting the differences in approaches to rebuilding local economies in places with varying levels of governmental capacity post-disaster to inform policymakers, scholars, and the disaster relief community as they plan their response to future disasters.
Introduces students to legalistic, theoretical, empirical, comparative and cross-disciplinary research methods, grounded in working examplesNew for this editionNew chapter on inter- and cross-disciplinary research essential reading for international students and students with a non-law first degree undertaking research in the areas of law, criminology, psychology and sociologyResearch ethics has been expanded to a full chapter that includes current plagiarism and imperfect disclosureBrings existing chapters up to date with the newest thinking in legal researchDrawing on actual research projects, Research Methods for Law discusses how legal research as process impacts on research as product.
The author team has a broad range of teaching and research experience in law, criminal justice and socio-legal studies, and give examples from real-life research products to illustrate the theory. The 27 full papers, 13 short papers, 9 posters and 9 demos presented in this volume were carefully reviewed and selected from initial submissions. In addition the book contains the abstract of 2 keynote speeches and an appendix stating information on the doctoral consortium, as well as the panel, which were held at the conference.
The papers are grouped in topical sections on networked information, semantics and interoperability, systems and architectures, text and multimedia retrieval, collaborative information spaces, DL applications and legal aspects, user interaction and information visualization, user studies, archives and repositories, europeana, and preservation.
By CustomerAs a starter in social science research, I really love this book. Before I read it, I knew all the statistical knowledge it includes and I had some some Stata experience. But this book is great because it showed me how to conduct social science research using these statistical knowledge and Stata, from raw dataset to running statistical tests. He has published more than articles in leading social and behavioral sciences journals. After reading this introductory text, you will be able to enter, build, and manage a data set as well as perform fundamental statistical analyses.
New to the Third Edition A new chapter on the analysis of missing data and the use of multiple-imputation methods Extensive revision of the chapter on ANOVA Additional material on the applicat
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