Chapter
2 Testing for types and antitypes
2.1 The binomial test and its approximations
2.1.1 Approximation of the binomial test using
2.1.2 Approximation of the binomial test using the DeMoivre-Laplace limit theorem
2.1.3 Standard normal approximation of the binomial test
2.1.4 Chi-square approximation of the z-test statistic
2.1.5 Heilmann and Schutt's F-approximation of the binomial test
2.2 Asymptotic CFA tests based on distributional assumptions
2.2.1 Lehmacher's asymptotic hypergeometrical test
2.2.2 Kiichenhoffs continuity correction of Lehmacher's asymptotic test
2.3 Comparison of CFA tests using empirical data
2.4 The problem of simultaneous testing in CFA: procedures for alpha adjustment
2.4.1 Alpha adjustment using Bonferroni's inequality
2.4.2 Holm's method for alpha adjustment
2.4.3 Hommel, Lehmacher, and Perlfs modifications of Holm's method
2.5 Application and comparison of procedures for alpha adjustment in CFA testing
3 Models of CFA: concepts and assumptions
3.1 The hierarchy of global CFA models
3.2.1 Interaction structure analysis
3.2.3 CFA of directed relations
3.2.4 Comparison of DCFA, ISA, and PCFA
Part II : Applications and Strategies of CFA
4 Global models of CFA: applications and examples
4.3 Second and higher order CFA
5 Regional models of CFA: applications and examples
5.1 Interaction structure analysis
5.1.1 Estimation of expected frequencies
5.1.3 Models of ISA and data examples
5.3 Special ISA application: independence of factorially defined tests
5.5 Application of PCFA: special issues
5.5.1 Conditional prediction CFA: stratifying on a variable
5.5.3 Prediction coefficients
5.6 Comparison of k samples
5.6.3. Combination of ISA and k-sample CFA
5.7 CFA of directed relationships
5.8 Aggregation of types and antitypes
Part III : Methods of Longitudinal CFA
6 CFA of change over time
6.2 CFA of shifts in location
6.3 CFA of first, second, and higher differences
6.3.1 CFA of first differences between t observation points
6.3.2 CFA of second and higher differences between t observation points
6.4 Considering both level and trend information
6.4.1 CFA of categories of trend and location
6.4.2 CFA of orthogonal polynomial coefficients for equidistant time points
6.4.3 CFA of orthogonal polynomial coefficients for nonequidistant time points
6.5 CFA of time series of different length
6.6 CFA in the analysis of treatment effects
6.7 CFA of treatment effects in control group designs
6.8 CFA of patterns of correlation or of distance sequences
Part IV : Strategies of CFA and computational issues
7 Exploratory and confirmatory search for types and antitypes
7.1 Exploratory and hybrid CFA
8 CFA and log-linear models
9.1 Programs for pocket calculators
9.2 Programs for microcomputers
9.3 Programs for main frame computers
Appendix A : Computational issues: the estimation of tail probabilities for the standard normal and the F distributions
The estimation of tail probabilities for the z statistic
The estimation of tail probabilities for the F statistic
Appendix B : Estimation of expected frequencies in 2 x 2 x 2 tables under the assumption that main effects and first order interactions exist
Appendix C : Critical alpha levels under Holm adjustment for up to 330 cells and a priori alphas 0.05 and 0.01
Introduction to Configural Frequency Analysis
：The Search for Types and Antitypes in Cross-Classification
( Environment and Behavior )
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