Improvements of the Gaussian quadrature in conjunction with the Newton-Raphson iteration technique (TM 000 789) are discussed as effective methods of calculating the bivariate normal correlation coefficient. (CK)

ORDMET is applicable to structures obtained from additive conjoint measurement designs, unfolding theory, general Fechnerian scaling, types of multidimensional scaling, and ordinal multiple regression. A description is obtained of the space containing all possible numerical representations which can satisfy the structure, size, and shape of which…

In this paper a reliable method is found for approximating the value of the Bivariate Normal Correlation Coefficient, rho, given values of the joint probability and the normal deviates, h and k, or the related areas. This technique finds useful application in the computation of the tetrachoric correlation coefficient, r, when the underlying…

This description of the technical details required for using the HIER-GRP computer program, which was developed to group or cluster regression equations in an iterative manner so as to minimize the overall loss of predictive efficiency at each iteration, contains a discussion of the basic algorithm, an outline of the essential steps,…

The program with extensive annotation is available in an unpublished dissertation (Schabert, 1970). (Authors)

A new basic algorithm is discussed that may be used to do factor analysis by any of these three methods: (1) unweighted least squares, (2) generalized least squares, or (3) maximum likelihood. (CK)

The absence of suitable external criteria is a recurrent problem for test, battery, and inventory developers in selecting items or tests for inclusion in final operational instruments. This report presents a computing algorithm developed for use when no adequate external selection criterion is available. The algorithm uses a multiple linear…

A method of nonmetric multidimensional scaling is described which minimizes pairwise departures from monotonicity. (Author)

The results of an algorithm which is designed to take a set of commonality coefficients, either real or manipulated, and, if possible, produce one or more sets of regressor correlations that are consistent with them are examined. A number of different ways of resolving the higher order commonality values into their lower orders were tried and the…

Under some circumstances, it is desirable to compare the factor patterns obtained from different factor analyses. To date, the best method of simultaneously achieving simple structure and maximum similarity is the technique devised by Bloxom (1968). This technique simultaneously rotates different factor patterns to maximum similarity and varimax…

Discusses the different strategies employed by three practical nonmetric multidimensional scaling algorithms using Monte Carlo techniques. (Author/RK)

Two factor analysis algorithms, previously described by P. Horst, have been programed for use on the General Electric Time-Sharing Computer System. The first of these, Principal Components Analysis (PCA), uses the Basic Structure Successive Factor Method With Residual Matrices algorithm to obtain the principal component vectors of a correlation…

Commonality analysis is an attempt to understand the relative predictive power of the regressor variables, both individually and in combination. The squared multiple correlation is broken up into elements assigned to each individual regressor and to each possible combination of regressors. The elements have the property that the appropriate sums…

A model and a computer program for performing conjoint measurement is developed. (AG)