Evaluating Chessboard MANOVA Designs Using Predictive and Matching Configural Frequency Analysis

This paper concerns the nonparametric evaluation of chessboard MANOVA designs. For this purpose, a matching procedure based on rook methodology is suggested as a complement to predictive coafigural frequency analysis. Using this procedure, a multivariate hypothesis can be tested in a single test. It is also possible to design a significance test to fit a specific composite hypothesis. The procedure is illustrated by results from a multivariate psychopharmacological experiment in which the effects of alcohol and caffeine were studied on test performance and volatility.     

A Note on a Continuity Correction for Testing in Three-Dimensional Configural Frequency Analysis

A continuity correction is proposed for the test statistics of HABERMAN (1978) and LEHMACHER (1981) for identifying overfrequented (or underfrequented) cells in the three-dimensional Configural Frequency Analysis (CFA). Its quality is shown by comparison with the test based on the exact distribution of the cell frequencies.     

A More Powerful Simultaneous Test Procedure in Configural Frequency Analysis

In the Configural Frequency Analysis (CFA) of KRAUTH and LIENERT (1973 a, b), overfrequented (or underfrequented) cells in multivariate contingency tables are identified by simultaneous binomial tests. As an alternative, finite and asymptotic tests are proposed, which are derived from the (exact conditional) generalized hypergeometrical distribution of the cell frequencies. These tests allow for considerably more powerful decisions than do the conservative binomial tests.     

Nonparametric Evaluation of ANOVA Designs by Local,Regional, and Global Contingency Testing

Nonparametric analysis of ANOVA designs is proposed to be done by simultaneous contingency testing of discretised response variables. Selected treatment-response patterns are evaluated by predictive configural frequency analysis (local contingency). Treatment response associations are defined by regional contingencies. Total treatment-response relation is defined by global contingency. All methods are illustrated numerically by biometrical examples.     

Nonparametric Comparison of Longitudinal Response Patterns from Unpaired Samples Using Configural Frequency Analysis

Nonparametric methods of Configural Frequency Analysis (CFA) for the comparison of longitudinal response patterns are discussed. In particular, methods of transforming response patterns into profiles that can be analyzed using CFA are presented. When two independent samples are given, two sample CFA can be applied to perform local testing. An example is given from research on obesity. Two sample CFA of response pattern is compared to methods of global testing.     

Test Procedures in Configural Frequency Analysis (CFA) Controlling the Local and Multiple Level

The test statistics used until now in the CFA have been developed under the assumption of the overall hypothesis of total independence. Therefore, the multiple test procedures based on these statistics are really only different tests of the overall hypothesis. If one likes to test a special cell hypothesis, one should only assume that this hypothesis is true and not the whole overall hypothesis. Such cell tests can then be used as elements of a multiple test procedure. In this paper it is shown that the usual test procedures can be very anticonservative (except of the two-dimensional, and, for some procedures, the three-dimensional case), and corrected test procedures are developed. Furthermore, for the construction of multiple tests controlling the multiple level, modifications of Holm's (1979) procedure are proposed which lead to sharper results than his general procedure and can also be performed very easily.     

Nonparametric Comparison of Longitudinal Response Patterns from Paired Samples Using Configural Frequency Analysis

Nonparametric methods of Configural Frequency Analysis (CFA) for comparing longitudinal response patterns are discussed. Characteristics of diagonally symmetric frequency distributions are mapped with hypotheses on the locus of treatment effects. Test statistics for the analysis of local dependencies are discussed. In particular, applications to paired samples are considered. A biomedical example is given from research on the effects of spasmolytic drugs. Local CFA-testing is compared with global testing. Alternative strategies of testing and the respective underlying assumptions are discussed.