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Languages : en
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Section 10.
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Section 10.
Author: George A. Marcoulides
Publisher: Psychology Press
ISBN: 113568412X
Category : Business & Economics
Languages : en
Pages : 479
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Book Description
This volume introduces the latest popular methods for conducting business research. The goal of each chapter author--a leading authority in a particular subject area--is to provide an understanding of each method with a minimum of mathematical derivations. The chapters are organized within three general interrelated topics--Measurement, Decision Analysis, and Modeling. The chapters on measurement discuss generalizability theory, latent trait and latent class models, and multi-faceted Rasch modeling. The chapters on decision analysis feature applied location theory models, data envelopment analysis, and heuristic search procedures. The chapters on modeling examine exploratory and confirmatory factor analysis, dynamic factor analysis, partial least squares and structural equation modeling, multilevel data analysis, modeling of longitudinal data by latent growth curve methods and structures, and configural models of longitudinal categorical data.
Author: Carol S. Aneshensel
Publisher: SAGE
ISBN: 1412994357
Category : Reference
Languages : en
Pages : 473
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This book presents the elaboration model for the multivariate analysis of observational quantitative data. This model entails the systematic introduction of "third variables" to the analysis of a focal relationship between one independent and one dependent variable to ascertain whether an inference of causality is justified. Two complementary strategies are used: an exclusionary strategy that rules out alternative explanations such as spuriousness and redundancy with competing theories, and an inclusive strategy that connects the focal relationship to a network of other relationships, including the hypothesized causal mechanisms linking the focal independent variable to the focal dependent variable. The primary emphasis is on the translation of theory into a logical analytic strategy and the interpretation of results. The elaboration model is applied with case studies drawn from newly published research that serve as prototypes for aligning theory and the data analytic plan used to test it; these studies are drawn from a wide range of substantive topics in the social sciences, such as emotion management in the workplace, subjective age identification during the transition to adulthood, and the relationship between religious and paranormal beliefs. The second application of the elaboration model is in the form of original data analysis presented in two Analysis Journals that are integrated throughout the text and implement the full elaboration model. Using real data, not contrived examples, the text provides a step-by-step guide through the process of integrating theory with data analysis in order to arrive at meaningful answers to research questions.
Author: Igor Chikalov
Publisher: Springer Science & Business Media
ISBN: 3642286674
Category : Technology & Engineering
Languages : en
Pages : 209
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Book Description
In this book, the following three approaches to data analysis are presented: - Test Theory, founded by Sergei V. Yablonskii (1924-1998); the first publications appeared in 1955 and 1958, - Rough Sets, founded by Zdzisław I. Pawlak (1926-2006); the first publications appeared in 1981 and 1982, - Logical Analysis of Data, founded by Peter L. Hammer (1936-2006); the first publications appeared in 1986 and 1988. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. - Logical Analysis of Data, founded by Peter L. Hammer (1936-2006); the first publications appeared in 1986 and 1988. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected.
Author: Rand R. Wilcox
Publisher: Springer
ISBN: 1441955259
Category : Social Science
Languages : en
Pages : 255
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Book Description
Conventional statistical methods have a very serious flaw. They routinely miss differences among groups or associations among variables that are detected by more modern techniques, even under very small departures from normality. Hundreds of journal articles have described the reasons standard techniques can be unsatisfactory, but simple, intuitive explanations are generally unavailable. Situations arise where even highly nonsignificant results become significant when analyzed with more modern methods. Without assuming the reader has any prior training in statistics, Part I of this book describes basic statistical principles from a point of view that makes their shortcomings intuitive and easy to understand. The emphasis is on verbal and graphical descriptions of concepts. Part II describes modern methods that address the problems covered in Part I. Using data from actual studies, many examples are included to illustrate the practical problems with conventional procedures and how more modern methods can make a substantial difference in the conclusions reached in many areas of statistical research. The second edition of this book includes a number of advances and insights that have occurred since the first edition appeared. Included are new results relevant to medians, regression, measures of association, strategies for comparing dependent groups, methods for dealing with heteroscedasticity, and measures of effect size.
Author: Peter Bühlmann
Publisher: Springer Science & Business Media
ISBN: 364220192X
Category : Mathematics
Languages : en
Pages : 568
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Book Description
Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This in-depth approach highlights the methods’ great potential and practical applicability in a variety of settings. As such, it is a valuable resource for researchers, graduate students and experts in statistics, applied mathematics and computer science.
Author: Vladimir Cherkassky
Publisher: John Wiley & Sons
ISBN: 9780470140512
Category : Computers
Languages : en
Pages : 560
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Book Description
An interdisciplinary framework for learning methodologies—covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied—showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text.
Author: Yu-Kang Tu
Publisher: Springer Science & Business Media
ISBN: 9400730241
Category : Medical
Languages : en
Pages : 315
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Book Description
Routine applications of advanced statistical methods on real data have become possible in the last ten years because desktop computers have become much more powerful and cheaper. However, proper understanding of the challenging statistical theory behind those methods remains essential for correct application and interpretation, and rarely seen in the medical literature. Modern Methods for Epidemiology provides a concise introduction to recent development in statistical methodologies for epidemiological and biomedical researchers. Many of these methods have become indispensible tools for researchers working in epidemiology and medicine but are rarely discussed in details by standard textbooks of biostatistics or epidemiology. Contributors of this book are experienced researchers and experts in their respective fields. This textbook provides a solid starting point for those who are new to epidemiology, and for those looking for guidance in more modern statistical approaches to observational epidemiology. Epidemiological and biomedical researchers who wish to overcome the mathematical barrier of applying those methods to their research will find this book an accessible and helpful reference for self-learning and research. This book is also a good source for teaching postgraduate students in medical statistics or epidemiology.
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Category : Sociology
Languages : en
Pages : 198
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Author: J. Scott Long
Publisher: SAGE Publications, Incorporated
ISBN: 9780803928060
Category : Social Science
Languages : en
Pages : 336
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Book Description
Statistical and methodological errors are fairly universal in all the social sciences. This unique volume investigates the following questions: what are the most common errors, and how can they be avoided? Common Problems/Proper Solutions identifies and corrects these errors and provides clear statements concerning methodological issues. Long groups the problems into two broad types: omission where researchers fail to apply methods ideal to a topic; and commission where a technique is inappropriately applied. Each article addresses a specific aspect of these problems. This volume encourages further communication between methodological specialists and quantitative researchers, and highlights the important relationship be
