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Models of Psychological Space, Heinrich Stumpf; John Eliot


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Цена: 14673.00р.
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Автор: Heinrich Stumpf; John Eliot
Название:  Models of Psychological Space
ISBN: 9781461291565
Издательство: Springer
Классификация:
ISBN-10: 1461291569
Обложка/Формат: Paperback
Страницы: 203
Вес: 0.31 кг.
Дата издания: 12.10.2011
Язык: English
Размер: 234 x 156 x 12
Основная тема: Psychology
Подзаголовок: Psychometric, Developmental, and Experimental Approaches
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Models of Psychological Space begins the reformulation of the construct of psychological space by bringing together in one volume a sampling of theoretical models from the psychometric, developmental, and experimental approaches.


Creating Models in Psychological Research

Автор: Olivier Mesly
Название: Creating Models in Psychological Research
ISBN: 3319157523 ISBN-13(EAN): 9783319157528
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This concise reference serves as a companion to traditional research texts by focusing on such essentials as model construction, robust methodologies and defending a compelling hypothesis.

Investigating the Psychological World: Scientific Method in the Behavioral Sciences

Автор: Haig Brian D.
Название: Investigating the Psychological World: Scientific Method in the Behavioral Sciences
ISBN: 0262027364 ISBN-13(EAN): 9780262027366
Издательство: MIT Press
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Цена: 6772.00 р.
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Описание:

A broad theory of research methodology for psychology and the behavioral sciences that offers a coherent treatment of a range of behavioral research methods.

This book considers scientific method in the behavioral sciences, with particular reference to psychology. Psychologists learn about research methods and use them to conduct their research, but their training teaches them little about the nature of scientific method itself. In Investigating the Psychological World, Brian Haig fills this gap. Drawing on behavioral science methodology, the philosophy of science, and statistical theory, Haig constructs a broad theory of scientific method that has particular relevance for the behavioral sciences. He terms this account of method the abductive theory of method (ATOM) in recognition of the importance it assigns to explanatory reasoning. ATOM offers the framework for a coherent treatment of a range of quantitative and qualitative behavioral research methods, giving equal treatment to data-analytic methods and methods of theory construction.

Haig draws on the new experimentalism in the philosophy of science to reconstruct the process of phenomena detection as it applies to psychology; he considers the logic and purpose of exploratory factor analysis; he discusses analogical modeling as a means of theory development; and he recommends the use of inference to the best explanation for evaluating theories in psychology. Finally, he outlines the nature of research problems, discusses the nature of the abductive method, and describes applications of the method to grounded theory method and clinical reasoning. The book will be of interest not only to philosophers of science but also to psychological researchers who want to deepen their conceptual understanding of research methods and methodological concerns.

Multiple Factor Analysis by Example Using R

Автор: Pages
Название: Multiple Factor Analysis by Example Using R
ISBN: 1482205475 ISBN-13(EAN): 9781482205473
Издательство: Taylor&Francis
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Цена: 13014.00 р.
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Описание: Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR). The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The next chapter discusses factor analysis for mixed data (FAMD), a little-known method for simultaneously analyzing quantitative and qualitative variables without group distinction. Focusing on MFA, subsequent chapters examine the key points of MFA in the context of quantitative variables as well as qualitative and mixed data. The author also compares MFA and Procrustes analysis and presents a natural extension of MFA: hierarchical MFA (HMFA). The final chapter explores several elements of matrix calculation and metric spaces used in the book.


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