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Configural Frequency Analysis
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Configural Frequency Analysis : Methods, Models, and Applications

Book Details

Format Hardback or Cased Book
ISBN-10 080584323X
ISBN-13 9780805843231
Publisher Taylor & Francis Inc
Imprint Psychology Press
Country of Manufacture US
Country of Publication GB
Publication Date Jun 1st, 2002
Print length 470 Pages
Weight 771 grams
Ksh 27,900.00
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This book provides an up-to-the-minute comprehensive intro to the methods, models, and applications of Configural Frequency Analysis (CFA). The book will serve as the main txt or supp txt for adv courses in CFA and other related subjects.
Configural Frequency Analysis (CFA) provides an up-to-the-minute comprehensive introduction to its techniques, models, and applications. Written in a formal yet accessible style, actual empirical data examples are used to illustrate key concepts. Step-by-step program sequences are used to show readers how to employ CFA methods using commercial software packages, such as SAS, SPSS, SYSTAT, S-Plus, or those written specifically to perform CFA.

CFA is an important method for analyzing results involved with categorical and longitudinal data. It allows one to answer the question of whether individual cells or groups of cells of cross-classifications differ significantly from expectations. The expectations are calculated using methods employed in log-linear modeling or a priori information. It is the only statistical method that allows one to make statements about empty areas in the data space.

Applied and or person-oriented researchers, statisticians, and advanced students interested in CFA and categorical and longitudinal data will find this book to be a valuable resource. Developed since 1969, this method is now used by a large number of researchers around the world in a variety of disciplines, including psychology, education, medicine, and sociology. Configural Frequency Analysis will serve as an excellent text for courses on configural frequency analysis, categorical variable analysis, or analysis of contingency tables. Prerequisites include an understanding of descriptive statistics, hypothesis testing, statistical model fitting, and some understanding of categorical data analysis and matrix algebra.

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