Towards an epistemology of religious traditions

Summary Starting from the acceptance of the Egalitarian Principle I exhibited a version which I considered too lax (BEP) and one I considered too strict (NEP), arriving at a version (MEP) which allows that there can be tolerance-limiting reasons for adhering to traditions but only if they are based on unreasoned knowledge claims. In fact, I hold that the situation most of us find ourselves in restricts such claims on religious topics to very general ones. Hence the choice between NEP and MEP is not significant. It follows that we should take up one of two positions concerning religious traditions: either we argue from the shared assumptions of a variety of traditions without genuine participation in any of them; or we justify participation in one of them by noting various marks of reliability, such as serendipitous understanding. A version of this paper was read at the Faith and Reason Conference held at the Catholic Institute in Strathfield, October 5 and 6, 1996. I would like to thank all who participated in the discussion of my paper on that occasion. I would also like to thank the anonymous referees for Sophia for their helpful comments.     

Methods for describing ordinal data with cardinal models

Several methods, both new and old, for describing ordinal data with a cardinal model are discussed in a newly developed and general context which broadens their applicability beyond their traditional use in multidimensional scaling. The relationships between the methods is investigated. It is shown that the two most commonly used methods (Guttman's rank-image principle and Kruskal's least-square monotonic transformation) are the boundary conditions of a newly proposed single parameter family of methods. An additional method is proposed which is shown to yield an equal-density model space. The commonly made distinction between “transformation” methods and “transformation-free” methods is shown to be a pseudodistinction. It is observed that all the methods can be stated as matrix operations on the model space with the conclusion that they try to optimize a linear combination of the model space.     

Nonmetric individual differences multidimensional scaling: An alternating least squares method with optimal scaling features

A new procedure is discussed which fits either the weighted or simple Euclidian model to data that may (a) be defined at either the nominal, ordinal, interval or ratio levels of measurement; (b) have missing observations; (c) be symmetric or asymmetric; (d) be conditional or unconditional; (e) be replicated or unreplicated; and (f) be continuous or discrete. Various special cases of the procedure include the most commonly used individual differences multidimensional scaling models, the familiar nonmetric multidimensional scaling model, and several other previously undiscussed variants.The procedure optimizes the fit of the model directly to the data (not to scalar products determined from the data) by an alternating least squares procedure which is convergent, very quick, and relatively free from local minimum problems.The procedure is evaluated via both Monte Carlo and empirical data. It is found to be robust in the face of measurement error, capable of recovering the true underlying configuration in the Monte Carlo situation, and capable of obtaining structures equivalent to those obtained by other less general procedures in the empirical situation.This project was supported in part by Research Grant No. MH10006 and Research Grant No. MH26504, awarded by the National Institute of Mental Health, DHEW. We wish to thank Robert F. Baker, J. Douglas Carroll, Joseph Kruskal, and Amnon Rapoport for comments on an earlier draft of this paper. Portions of the research reported here were presented to the spring meeting of the Psychometric Society, 1975. ALSCAL, a program to perform the computations discussed in this paper, may be obtained from any of the authors.Jan de Leeuw is currently at Datatheorie, Central Rekeninstituut, Wassenaarseweg 80, Leiden, The Netherlands. Yoshio Takane can be reached at the Department of Psychology, University of Tokyo, Tokyo, Japan.     

A three-year follow-up of older adult participants in a memory-skills training program

This study examined the long-term effects of participation in a self-taught memory training program. In all, 27 memory training and 13 nontraining participants were assessed at approximately 3-year follow-ups. Assessment of these groups prior to the introduction of training had revealed nonsignificant differences in memory performance but marked differences in level of memory complaints, with training participants evidencing higher levels of complaints. The current assessment again demonstrated overall nonsignificant differences in memory performance but significant differences in memory complaints between the two groups. More specifically, the training group evidenced significant decreases in memory performance over the 3-year interval, but no significant changes in memory complaints were observed for either group. Thus, memory training appeared to have little long-term effect on memory functioning. Future research should explore long-term maintenance strategies in memory training with older adults.     

Three notes on ALSCAL

It is reported that (1) a new coordinate estimation routine is superior to that originally proposed for ALSCAL; (2) an oversight in the interval measurement level case has been found and corrected; and (3) a new initial configuration routine is superior to the original.     

Increased Reinforcer Immediacy can Promote Employment-Seeking in Unemployed Homeless Adults with Alcohol Use Disorder

The Psychological Record - Unemployment, homelessness, and substance use are interrelated. The present study took place as part of a clinical trial intended to promote employment and abstinence...     

Enhancing dynamic graphical analysis with the Lisp-Stat language and the ViSta statistical program

Presented is a sample of computerized methods aimed at multidimensional scaling and psychometric item analysis that offer a dynamic graphical interface to execute analyses and help visualize the results. These methods show how the Lisp-Stat programming language and the ViSta statistical program can be jointly applied to develop powerful computer applications that enhance dynamic graphical analysis methods. The feasibility of this combined strategy relies on two main features: (1) The programming architecture of ViSta enables users to add new statistical methods as plug-ins, which are integrated into the program environment and can make use of all the functions already available in ViSta (e.g., data manipulation, editing, printing); and (2) the set of powerful statistical and graphical functions integrated into the Lisp-Stat programming language provides the means for developing statistical methods with dynamic graphical visualizations, which can be implemented as ViSta plug-ins.