Configural Frequency Analysis: Foundations, Models, and Applications

Preface
Contents
Chapter 1: Questions that Can Be Answered with CFA
	References
Chapter 2: Elements of CFA
	2.1 Lienert´s Version of CFA
	2.2 Log-Linear Models for the Estimation of Expected Cell Frequencies in CFA
	2.3 CFA Base Models and Their Design Matrices
	2.4 Base Models of CFA
		2.4.1 A Classification of Base Models for CFA
		2.4.2 Global CFA Base Models
		2.4.3 Regional Models of CFA
		2.4.4 Multi-Step CFA Models
	2.5 CFA of Transformed Data
	2.6 CFA Under Consideration of Special Variables
	2.7 Testing Hypotheses in CFA
		2.7.1 CFA Significance Tests
		2.7.2 The Exact Binomial Test
		2.7.3 Approximative Tests
		2.7.4 Tests for Groups of Configurations
		2.7.5 Protecting the Significance Level α
		2.7.6 Methods for the Protection of α
	2.8 The Four Steps of CFA
	References
Chapter 3: Models of CFA
	3.1 Global CFA Models
		3.1.1 Zero Order CFA
		3.1.2 First Order CFA
		3.1.3 Second and Higher Order CFA
		3.1.4 Global CFA After Removal of a Group of Effects
	3.2 Regional Models of CFA
		3.2.1 Finding Groups of Variables for CFA
		3.2.2 Prediction CFA
		3.2.3 Bi-Prediction CFA
		3.2.4 Comparing Groups of Data Carriers
			3.2.4.1 Two-Group CFA
			3.2.4.2 Descriptive Measures for Two-Group CFA
				Gonzles-Debén´s Effect Strength π*
				Rosenthal and Rubin´s Binomial Effect Strength (BES)
			3.2.4.3 Three Ways to Deviate from Independence
			3.2.4.4 CFA for the Comparison of Multiple Groups
	References
Chapter 4: Models of Longitudinal CFA
	4.1 CFA of Differences
		4.1.1 Difference Scores
		4.1.2 CFA of Differences
		4.1.3 Expected Frequencies in the Analysis of Difference Variables
	4.2 Level, Variability, and Shape of Series of Measures
		4.2.1 CFA of Change in Level of Series of Measures
		4.2.2 CFA of Variability of Series of Measures
		4.2.3 CFA of Polynomial Parameters
		4.2.4 Series of Scores that Differ in Length
	4.3 CFA in Quasi-Experimental and in Experimental Designs
		4.3.1 CFA and Designs with no Control Group
		4.3.2 CFA of Data from Control Group Designs
	4.4 Confirmatory CFA of Longitudinal Data
	4.5 CFA of Longitudinal Correlations or Distances
	4.6 Prediction in Longitudinal Data
		4.6.1 Predicting the End Point of a Series of Scores
		4.6.2 Predicting a Trajectory with CFA
		4.6.3 Predicting One Trajectory from another
	4.7 Auto-Association CFA
	4.8 Predicting the Shape of a Curve: The Case of Multiple Predictors
	4.9 CFA of Lags: Intra-Individual Series of Scores
	4.10 Functions as CFA Base Models
	References
Chapter 5: Designs for CFA
	5.1 Fractional Factorial Designs for CFA
		5.1.1 Fractional Factorial Designs: An Introduction
		5.1.2 Creating Fractional Factorial Designs
		5.1.3 Fractional Factorial Designs in CFA
	5.2 Structural Zeros in CFA
		5.2.1 Incomplete Tables and Separability
		5.2.2 Design-Specific Structural Zeros
	References
Chapter 6: Special Variables in CFA
	6.1 Covariates in CFA
	6.2 CFA with Ordinal Variables
		6.2.1 Iterative Proportional Fitting
		6.2.2 The Linear-by-Linear Association Model
	6.3 Moderator Variables in CFA
	6.4 Mediator CFA
		6.4.1 Significance Testing of the Indirect Effect
		6.4.2 Evaluating Mediator Hypotheses
		6.4.3 Causal Mediator Analysis
		6.4.4 Mediator Models for Categorical Variables
		6.4.5 Configural Mediation Analysis
			6.4.5.1 Pattern-Specific Mediation Models
			6.4.5.2 von Eye et al.´s (2009) Method of Mediation Analysis
			6.4.5.3 Smyth and MacKinnon´s (2020) Modifications
			6.4.5.4 Wiedermann and von Eye´s (2020) Method
	References
Chapter 7: The Treasure Chest of CFA
	7.1 Alternative Approaches to CFA
		7.1.1 Victor´s Alternative Exploratory CFA
		7.1.2 von Eye and Mair´s Alternative Sequential CFA
	7.2 Functional CFA
		7.2.1 Functional CFA I: The Ascending, Inclusive Strategy
		7.2.2 Functional CFA II: The Descending Excluding Strategy
	7.3 CFA and Tree Structures
	7.4 Rater Agreement
	7.5 CFA of Large Sparse Tables
	7.6 CFA as Test of Multivariate Normality
	7.7 Latent Class Analysis and CFA
	7.8 CFA and Causality
		7.8.1 Forms of Causal Relations
		7.8.2 CFA and Granger Causality
	7.9 CFA of Intensive Longitudinal Data
	7.10 Bayes CFA
		7.10.1 Bayes Definition of Types and Antitypes
		7.10.2 Patterns of Types and Antitypes
	7.11 Limits of CFA: Issues and Countermeasures
	References
Chapter 8: Software for CFA
	8.1 CFA Fortran Program
	8.2 R Packages and Modules
		8.2.1 Global CFA Base Models
		8.2.2 Prediction CFA
		8.2.3 Two-Group CFA
		8.2.4 Bayes CFA
	References
References
Index