Multiple Regression A Primer Research Methods And Statistics
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Multiple Regression
Presenting topics in the form of questions and answers, this popular supplemental text offers a brief introduction on multiple regression on a conceptual level. Author Paul D. Allison answers the most essential questions (such as how to read and interpret multiple regression tables and how to critique multiple regression results) in the early chapters, and then tackles the less important ones (for instance, those arising from multicollinearity) in the later chapters. With this organization, readers can stop at the end of any chapter and still feel like they′ve already gotten the meat of the subject.
The SAGE Encyclopedia of Social Science Research Methods
"This defining work will be valuable to readers and researchers in social sciences and humanities at all academic levels. As a teaching resource it will be useful to instructors and students alike and will become a standard reference source. Essential for general and academic collections."--CHOICE"Appreciative users of this volume will be students, faculty, and researchers in academic, special, and large public libraries, for whom it is recommended."--LIBRARY JOURNALSAGE Reference is proud to announce The SAGE Encyclopedia of Social Science Research Methods, a three-volume resource that is a first of its kind, developed by the leading publisher of social science research methods books and journals. This unique multi-volume reference set offers readers an all-encompassing education in the ways of social science researchers. Written to be accessible to general readers, entries do not require any advanced knowledge or experience to understand the purposes and basic principles of any of the methods. The Encyclopedia features two major types of entries: definitions, consisting of a paragraph or two, provide a quick explanation of a methodological term; and topical treatments or essays discussing the nature, history, application/example and implication of using a certain method. Also included are suggested readings and references for future study. To help provide a more complete explanation than is often achieved within the scope of a single article, key terms and concepts appear in SMALL CAPITAL LETTERSto refer readers to related terms explained elsewhere. In addition to epistemological issues that influence the nature of research questions and assumptions, The SAGE Encyclopedia of Social Science Research Methods tackles topics not normally viewed as part of social science research methodology, from philosophical issues such as poststructuralismto advanced statistical techniques. In covering the full range of qualitative and quantitative data analyses, this key reference offers an integrated approach that allows the reader to choose the most appropriate and robust techniques to apply to each situation. Many entries treat traditional topics in a novel way, stimulating both interest and new perspectives. One example is the entry Econometrics, by Professor DamodarGujarati. Following a process which many educators preach but seldom practice, Gujarati walks the reader twice through the research process from economic theory to data and models to analysis, once in principle and a second time with an example. In using the ordinary process of economic research to achieve an extraordinary impact, he leaves the reader thinking not only about methods and models but also the fundamental purpose of econometrics. Topics Covered Analysis of Variance Association and Correlation Basic Qualitative Research Basic Statistics Causal Modeling (Structural Equations) Discourse/Conversation Analysis Econometrics Epistemology Ethnography Evaluation Event History Analysis Experimental Design Factor Analysis & Related Techniques Feminist Methodology Generalized Linear Models Historical/Comparative Interviewing in Qualitative Research Latent Variable Model Life History/Biography LoglinearModels (Categorical Dependent Variables) Longitudinal Analysis Mathematics and Formal Models Measurement Level Measurement Testing & Classification Multiple Regression Multilevel Analysis Qualitative Data Analysis Sampling in Surveys Sampling in Qualitative Research Scaling Significance Testing Simple Regression Survey Design Time Series Key Features Over 900 entries arranged A to Z Each entry is written by a leading authority in the field, covering both quantitative and qualitative methods Covers all disciplines within the social sciences Contains both concise definitions and in-depth essays Three volumes and more than 1500 pages
The SAGE Handbook of Quantitative Methods in Psychology
`I often... wonder to myself whether the field needs another book, handbook, or encyclopedia on this topic. In this case I think that the answer is truly yes. The handbook is well focused on important issues in the field, and the chapters are written by recognized authorities in their fields. The book should appeal to anyone who wants an understanding of important topics that frequently go uncovered in graduate education in psychology′ - David C Howell, Professor Emeritus, University of Vermont Quantitative psychology is arguably one of the oldest disciplines within the field of psychology and nearly all psychologists are exposed to quantitative psychology in some form. While textbooks in statistics, research methods and psychological measurement exist, none offer a unified treatment of quantitative psychology. The SAGE Handbook of Quantitative Methods in Psychology does just that. Each chapter covers a methodological topic with equal attention paid to established theory and the challenges facing methodologists as they address new research questions using that particular methodology. The reader will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area. Drawing on a global scholarship, the Handbook is divided into seven parts: Part One: Design and Inference: addresses issues in the inference of causal relations from experimental and non-experimental research, along with the design of true experiments and quasi-experiments, and the problem of missing data due to various influences such as attrition or non-compliance. Part Two: Measurement Theory: begins with a chapter on classical test theory, followed by the common factor analysis model as a model for psychological measurement. The models for continuous latent variables in item-response theory are covered next, followed by a chapter on discrete latent variable models as represented in latent class analysis. Part Three: Scaling Methods: covers metric and non-metric scaling methods as developed in multidimensional scaling, followed by consideration of the scaling of discrete measures as found in dual scaling and correspondence analysis. Models for preference data such as those found in random utility theory are covered next. Part Four: Data Analysis: includes chapters on regression models, categorical data analysis, multilevel or hierarchical models, resampling methods, robust data analysis, meta-analysis, Bayesian data analysis, and cluster analysis. Part Five: Structural Equation Models: addresses topics in general structural equation modeling, nonlinear structural equation models, mixture models, and multilevel structural equation models. Part Six: Longitudinal Models: covers the analysis of longitudinal data via mixed modeling, time series analysis and event history analysis. Part Seven: Specialized Models: covers specific topics including the analysis of neuro-imaging data and functional data-analysis.