Describes a new combinatorial algorithm for fitting additive trees to proximity data. This generalized triples method examines all triples of objects of interest in relation to the remaining set of objects to be clustered. The procedure is illustrated, and a simulation study shows its advantages. (SLD)

The cross-validated classification accuracies of three predictor weighting strategies (least squares, ridge regression, and reduced rank) were compared under varying simulated data conditions for the two-group classification problem. Results were somewhat similar to previous findings with multiple regression when absolute rather than relative…

A simulation study was conducted to determine whether latent class model parameters are recovered adequately by Latent Transition Analysis (LTA). Results indicate that parameter recovery is satisfactory overall and that the benefits of adding indicators outweigh the costs. Additional indicators also improve standard errors. An example of LTA is…

A mathematical formula is introduced for the effect of integrating data. A method is then derived to eliminate the effect from correlations of variables, including mean composites, thus allowing for a clustering algorithm that requires allocation of variables according to the magnitude of their correlations. Examples illustrate the procedure. (SLD)

Seven data sets (namely, clinical data on children) were subjected to clustering by seven algorithms--the B-coefficient, Linear Typal Analysis; elementary linkage analysis, Numerical Taxonomy System, Statistical Analysis System hierarchical clustering method, Taxonomy, and Bolz's Type Analysis. The little-known B-coefficient method compared…