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基本説明
Shows how to use the latest configural frequency analysis (CFA) techniques to analyze categorical data.
Full Description
Using real-world data examples, this authoritative book shows how to use the latest configural frequency analysis (CFA) techniques to analyze categorical data. Some of the techniques are presented here for the first time. In contrast to methods that focus on relationships among variables, such as log-linear modeling, CFA allows researchers to evaluate differences and change at the level of individual cells in a table. Illustrated are ways to identify and test for cell configurations that are either consistent with or contrary to hypothesized patterns (the types and antitypes of CFA); control for potential covariates that might influence observed results; develop innovative prediction models; address questions of moderation and mediation; and analyze intensive longitudinal data. The book also describes free software applications for executing CFA.
Contents
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1. Introduction
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1.1 Questions That CFA Can Answer
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1.2 The Five Steps of CFA
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1.3 Introduction to CFA: An Overview
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1.4 Chapter Summary
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2. Configural Analysis of Rater Agreement
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2.1 Rater Agreement CFA
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2.2 Data Examples
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2.3 Chapter Summary
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3. Structural Zeros in CFA
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3.1 Blanking Out Structural Zeros
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3.2 Structural Zeros by Design
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3.2.1 Polynomials and the Method of Differences
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3.2.2 Identifying Zeros That Are Structural by Design
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3.3 Chapter Summary
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4. Covariates in CFA
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4.1 CFA and Covariates
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4.2 Chapter Summary
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5. Configural Prediction Models
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5.1 Logistic Regression and Prediction CFA
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5.1.1 Logistic Regression
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5.1.2 Prediction CFA
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5.1.3 Comparing Logistic Regression and P-CFA Models
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5.2 Predicting an End Point
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5.3 Predicting a Trajectory
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5.4 Graphical Presentation of Results of P-CFA Models
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5.5 Chapter Summary
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6. Configural Mediator Models
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6.1 Logistic Regression plus Mediation
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6.2 CFA-Based Mediation Analysis
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6.3 Configural Chain Models
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6.4 Chapter Summary
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7. Auto-Association CFA
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7.1 A-CFA without Covariates
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7.2 A-CFA with Covariates
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7.2.1 A-CFA with Covariates I: Types and Antitypes Reflect Any of the Possible Relationships between Two or More Series of Measures
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7.2.2 A-CFA with Covariates II: Types and Antitypes Reflect Only Relationships between the Series of Measures and the Covariate
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7.3 Chapter Summary
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8. Configural Moderator Models
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8.1 Configural Moderator Analysis: Base Models with and without Moderator
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8.2 Longitudinal Configural Moderator Analysis under Consideration of Auto-Associations
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8.3 Configural Moderator Analysis as n-Group Comparison
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8.4 Moderated Mediation
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8.5 Graphical Representation of Configural Moderator Results
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8.6 Chapter Summary
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9. The Validity of CFA Types and Antitypes
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9.1 Validity in CFA
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9.2 Chapter Summary
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10. Functional CFA
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10.1 F-CFA I: An Alternative Approach to Exploratory CFA (Sequential Identification of Types and Antitypes)
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10.1.1 Kieser and Victor's Alternative, Sequential CFA: Focus on Model Fit
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10.1.2 von Eye and Mair's Sequential CFA: Focus on Residuals
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10.2 Special Case: One Dichotomous Variable
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10.3 F-CFA II: Explaining Types and Antitypes
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10.3.1 Explaining Types and Antitypes: The Ascending, Inclusive Strategy
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10.3.2 Explaining Types and Antitypes: The Descending, Exclusive Strategy
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10.4 Chapter Summary
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11. CFA of Intensive Categorical Longitudinal Data
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11.1 C
