Download PDF BookExploratory Factor Analysis (Understanding Statistics)

Ebook Exploratory Factor Analysis (Understanding Statistics)

Ebook Exploratory Factor Analysis (Understanding Statistics)

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Book Details :
Published on: 2011-12-22
Released on: 2011-12-22
Original language: English

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, business, sociology, education, political science, and communications. To a lesser extent, it has also been utilized within the physical and biological sciences. Despite its long and widespread usage in many domains, numerous aspects of the underlying theory and application of EFA are poorly understood by researchers. Indeed, perhaps no widely used quantitative method requires more decisions on the part of a researcher and offers as wide an array of procedural options as EFA does. This book provides a non-mathematical introduction to the underlying theory of EFA and reviews the key decisions that must be made in its implementation. Among the issues discussed are the use of confirmatory versus exploratory factor analysis, the use of principal components analysis versus common factor analysis, procedures for determining the appropriate number of factors, and methods for rotating factor solutions. Explanations and illustrations of the application of different factor analytic procedures are provided for analyses using common statistical packages (SPSS and SAS), as well as a free package available on the web (Comprehensive Exploratory Factor Analysis). In addition, practical instructions are provided for conducting a number of useful factor analytic procedures not included in the statistical packages. Exploratory Factor Analysis with R - Statpower Exploratory Factor Analysis with R James H. Steiger Exploratory Factor Analysis with R can be performed using the factanal function. Principal Component Analysis and Exploratory Factor ... About the Instructor. Karen Grace-Martin is the workshop instructor and founder of The Analysis Factor. Karen helps statistics practitioners gain an intuitive ... Understanding and Using Factor Scores: Considerations for ... Practical Assessment Research & Evaluation Vol 14 No 20 Page 3 DiStefano Zhu & Mndril Computing factor Scores a factor are given equal weight regardless of ... Factor Analysis in R Advanced Statistics Quick-R Principal Components and Factor Analysis . This section covers principal components and factor analysis. The later includes both exploratory and confirmatory methods. Factor Analysis: A Short Introduction Part 1 Factor analysis is a useful tool for investigating variable relationships for complex concepts such as socioeconomic status dietary patterns or psychological scales ... Exploratory data analysis - Wikipedia In statistics exploratory data analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics often with visual methods. The Analysis Factor Statistical Consulting Resources ... One of the many confusing issues in statistics is the confusion between Principal Component Analysis (PCA) and Factor Analysis (FA). They are very similar in many ... Factor Analysis - Statistics Solutions Factor Analysis. Factor analysis is a technique that is used to reduce a large number of variables into fewer numbers of factors. This technique extracts maximum ... Confirmatory factor analysis - Wikipedia In statistics confirmatory factor analysis (CFA) is a special form of factor analysis most commonly used in social research. It is used to test whether measures of ... Confirmatory Factor Analysis - Statistics Solutions Confirmatory Factor Analysis. Confirmatory factor analysis (CFA) is a multivariate statistical procedure that is used to test how well the measured variables ...
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