N.-Y.: Wiley, 2011. - 294p.
Latent Variable Models and Factor Analysis provides a comprehensive and unified approach to factor analysis and latent variable modeling from a statistical perspective. This book presents a general framework to enable the derivation of the commonly used models, along with updated numerical examples. Nature and interpretation of a latent variable is...
NY: Wiley-Interscience, 1994. — 755 p. Statistical Factor Analysis and Related Methods Theory and Applications In bridging the gap between the mathematical and statistical theory of factor analysis, this new work represents the first unified treatment of the theory and practice of factor analysis and latent variable models. It focuses on such areas as: The classical principal...
New York: Springer, 1978. — 634 p. The Position of Factor Analysis in Psychological Research. Extracting Factors: The Algebraic Picture. Rotating Factors: The Geometric Picture. Fixing the Number of Factors: The Scientific Model. Fixing the Number of Factors: The Most Practicable Psychometric Procedures. The Theory of Unique Rotational Resolution by Confactor, Procrustes, and...
2nd Edition. — Cassell Academic, 1990. — 132 р. — ISBN 0-304-32331-4. Factor analysis is an increasingly important tool for understanding and working with quantitative data. It is used in education (for analysing exam results), psychology, medical science, economics and other scientific fields, and allows one to work with statistics from an area where many variables are...
New York: Psychology Press, 2009. — 452 p. — ISBN 1315827506, 9781315827506. The goal of this book is to foster a basic understanding of factor analytic techniques so that readers can use them in their own research and critically evaluate their use by other researchers. Both the underlying theory and correct application are emphasized. The theory is presented through the...
Lawrence Erlbaum Associates, publishers. 2007. — 384 p. — ISBN: 0805862129. Factor analysis is one of the success stories of statistics in the social sciences. The reason for its wide appeal is that it provides a way to investigate latent variables, the fundamental traits and concepts in the study of individual differences. Factor Analysis in the Year 2004: Still Spry at 100...
New York: Psychology Press, 1993. — 480 p. This book is written primarily as a text for a course in factor analysis at the advanced undergraduate or graduate level. It is most appropriate for students of the behavioral and social sciences, though colleagues and students in other disciplines also have used preliminary copies. It does not pretend to be a comprehensive treatise....
London: Chapman and Hall, 1984. — 116 p. — ISBN 940108954X, 9789401089548 Latent variable models are used in many areas of the social and behavioural sciences, and the increasing availability of computer packages for fitting such models is likely to increase their popularity. This book attempts to introduce such models to applied statisticians and research workers interested in...
Oxford: Oxford University Press, 2011. — 170 p. Exploratory Factor Analysis (EFA) has played a major role in research conducted in the social sciences for more than 100 years, dating back to the pioneering work of Spearman on mental abilities. Since that time, EFA has become one of the most commonly used quantitative methods in many of the social sciences, including psychology,...
New York: Taylor & Francis, 2015. — 465 p. Comprehensive and comprehensible, this classic text covers the basic and advanced topics essential for using factor analysis as a scientific tool in psychology, education, sociology, and related areas. Emphasizing the usefulness of the techniques, it presents sufficient mathematical background for understanding and applying its use....
Sage Publications, Incorporated, 2019. — 145 p. A firm knowledge of factor analysis is key to understanding much published research in the social and behavioral sciences. Exploratory Factor Analysis by W. Holmes Finch provides a solid foundation in exploratory factor analysis (EFA), which along with confirmatory factor analysis, represents one of the two major strands in this...
CRC Press, 2015. — 268 p. An introduction to exploratory techniques for multivariate data analysis, this book covers the key methodology, including principal components analysis, correspondence analysis, mixed models and multiple factor analysis. The authors take a practical approach, with examples leading the discussion of the methods and lots of graphics to emphasize...
New York: Springer. – 2002. – 518 p. Principal component analysis is probably the oldest and best known of the techniques of multivariate analysis. It was first introduced by Pearson (1901), and developed independently by Hotelling (1933). Like many multivariate methods, it was not widely used until the advent of electronic computers, but it is now well entrenched in virtually...
2nd edition. — London Butterworths, 1971. — ISBN 0408701528. Table of contents: The Scope of Factor Analysis Parameters in Factor Models Principal Component Analysis Estimation in the Unrestricted Model Sampling Formulae for the Unrestricted Model Factor Transformation and Interpretation Estimation in Restricted Factor Models The Estimation of Factor Scores Identifying Factors...
Sage Publications, 2021. — 145 p. Measurement connects theoretical concepts to what is observable in the empirical world, and is fundamental to all social and behavioral research. In this volume, J. Micah Roos and Shawn Bauldry introduce a popular approach to measurement: Confirmatory Factor Analysis (CFA). As the authors explain, CFA is a theoretically informed statistical...
Hauppauge: Nova Science Publishers, Inc., 2017. — 215 p. Exploratory Factor Analysis: An Overview Abstract Exploratory or Confirmatory Factor Analysis? Common Factors or Principal Components? The Common Factor Model Are Data Appropriate for Factor Analysis? Considerations Related to the Observed Variables Considerations Related to the Sample Steps and Decisions in the...
New York: Springer-Verlag, 1996. — 232 p. — ISBN 1461284554, 9781461284550 During the last two decades, structural equation modeling (SEM) has emerged as a powerful multivariate data analysis tool in social science research settings, especially in the fields of sociology, psychology, and education. Although its roots can be traced back to the first half of this century, when...
NY: Chapman and Hall/CRC, 2009. — 524 p. — (Statistics in the Social and Behavioral Sciences Series). — ISBN: 978-1-4200-9981-2. Providing a practical, thorough understanding of how factor analysis works, Foundations of Factor Analysis, Second Edition discusses the assumptions underlying the equations and procedures of this method. It also explains the options in commercial...
Cambridge, Cambridge University Press, 1996. — 583 p. Монография посвящена применению метода факторного анализа в естественных науках. Рассматриваются основные идеи факторного анализа, математические основы, R, Q, и R-Q подходы к формированию матрицы данных, интерпретация данных. Приведены примеры анализа и обсуждение вычислительных программ. Для изучающих многомерные...
London University Press, 1951. — 422 p. The analysis of tests . The theory of two factors. Multiple-factor analysis. The sampling theory. The geometrical picture. Hotelling's " principal components. The estimation of factors . Estimation and the pooling square. The estimation of factors by regression. Maximizing and minimizing the specifics. The influence of sampling and...
Chicago: University of Chicago Press, 1947. — 555 p. Mathematical Introduction The Factor Problem Fundamental Equations Geometrical Models A Factor Problem in Two Dimensions The Grouping Method of Factoring Factors as Explanatory Concepts The Spherical Model The Centroid Method of Factoring Configurations and Factor Patterns Rotation of Axes The Method of Extended Vectors The...
L.: Tucker, 1997. - 459p.
Монография посвящена методу факторного анализа и его применению для нахождения взаимосвязей в многомерных данных. Рассмотрены алгебраические и статистические свойства модели, факторные вращения как графическими, так и аналитическими методами, приложения факторного анализа.
Для изучающих применение многомерных статистических методов.
Routledge, Taylor & Francis, 2021. — 199 p. — ISBN 978-0-367-63625-8. This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using the open source software R. In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots of R and RStudio code, and recommends evidence-based best...
2nd edition. — Boca Raton: CRC Press, 2017. — 731 p. Requiring no prior training, Modern Statistics for the Social and Behavioral Sciences provides a two-semester, graduate-level introduction to basic statistical techniques that takes into account recent advances and insights that are typically ignored in an introductory course. Hundreds of journal articles make it clear that...
М.: Статистика, 1975. — 329 с. Уникальное по своему содержанию пособие, ориентированное не только для производственников, но и для всех тех, кто желает освоить основные методы статистики. В частности, подробнейшее описание методов с многочисленными примерами делает его полезным для биологов, медиков, социологов, психологов, и т.д. Весьма подробно рассмотрены основные виды...
Пер. с нем. В.М. Ивановой. — Предисловие А.М. Дуброва. — М.: Статистика, 1980. — 398 с.: ил. — (Математико-статистические методы за рубежом). Книга посвящена многомерному статистическому анализу. В ней в комплексе рассматриваются факторный, компонентный, дискриминантный и другие виды анализа. Представлены современные методы оценки весовых коэффициентов, интерпретация факторных...
М.: Мир, 1967. - 144 с., OCR. Настоящая монография даёт чёткое представление о задачах факторного анализа, который находит всё большее применение при решении различных практических задач. Факторный анализ возник и развивался в связи с решением в первую очередь задач психологии (например, объяснение успеваемости учеников). Однако область его приложений значительно шире и...
М.: Либроком, 2013. — 174 с. — ISBN: 978-5-397-03264-3, OCR. Настоящее издание посвящено обоснованию практического использования факторного анализа (ФА) в различных сферах деятельности. ФА является результатом дальнейшего развития многомерных статистических методов, таких как корреляционный анализ, дисперсионный анализ, регрессионный анализ и другие методы, которые определенным...
Москва: Статистика, 1974. — 200 с. Общая характеристика факторного анализа как научного метода Математические основы факторного анализа Некоторые основные положения теории факторного анализа Центроидный метод определения факторов Вращение системы координат Интерпретация факторов Другие методы определения факторов Различные техники проведения факторного эксперимента Зависимые...
Москва: Статистика, 1972. — 489 с. Книга разделена на пять основных частей, посвященных соответственно основам факторного анализа, прямым факторным решениям, преобразованным факторным решениям, некоторым специальным разделам, задачам и упражнениям. В шести главах части I даны предыстория и основные понятия факторного анализа, излагаются разделы математики, необходимые для...
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