Generalized structured component analysis

We propose an alternative method to partial least squares for path analysis with components, called generalized structured component analysis. The proposed method replaces factors by exact linear combinations of observed variables. It employs a well-defined least squares criterion to estimate model parameters. As a result, the proposed method avoids the principal limitation of partial least squares (i.e., the lack of a global optimization procedure) while fully retaining all the advantages of partial least squares (e.g., less restricted distributional assumptions and no improper solutions). The method is also versatile enough to capture complex relationships among variables, including higher-order components and multi-group comparisons. A straightforward estimation algorithm is developed to minimize the criterion.The work reported in this paper was supported by Grant A6394 from the Natural Sciences and Engineering Research Council of Canada to the second author. We wish to thank Richard Bagozzi for permitting us to use his organizational identification data and Wynne Chin for providing PLS-Graph 3.0.     

A multivariate reduced-rank growth curve model with unbalanced data

A multivariate reduced-rank growth curve model is proposed that extends the univariate reducedrank growth curve model to the multivariate case, in which several response variables are measured over multiple time points. The proposed model allows us to investigate the relationships among a number of response variables in a more parsimonious way than the traditional growth curve model. In addition, the method is more flexible than the traditional growth curve model. For example, response variables do not have to be measured at the same time points, nor the same number of time points. It is also possible to apply various kinds of basis function matrices with different ranks across response variables. It is not necessary to specify an entire set of basis functions in advance. Examples are given for illustration.The work reported in this paper was supported by Grant A6394 from the Natural Sciences and Engineering Research Council of Canada to the second author. We thank Jennifer Stephan for her helpful comments on an earlier version of this paper. We also thank Patrick Curran and Terry Duncan for kindly letting us use the NLSY and substance use data, respectively. The substance use data were provided by Grant DA09548 from the National Institute on Drug Abuse.     

Kernel smoothing approaches to nonparametric item characteristic curve estimation

The option characteristic curve, the relation between ability and probability of choosing a particular option for a test item, can be estimated by nonparametric smoothing techniques. What is smoothed is the relation between some function of estimated examinee ability rankings and the binary variable indicating whether or not the option was chosen. This paper explores the use of kernel smoothing, which is particularly well suited to this application. Examples show that, with some help from the fast Fourier transform, estimates can be computed about 500 times as rapidly as when using commonly used parametric approaches such as maximum marginal likelihood estimation using the three-parameter logistic distribution. Simulations suggest that there is no loss of efficiency even when the population curves are three-parameter logistic. The approach lends itself to several interesting extensions.The author wishes to acknowledge the support of the National Sciences and Engineering Research Council of Canada through grant A320 and the support of Educational Testing Service during his leave there.     

Multidimensional successive categories scaling: A maximum likelihood method

A single-step maximum likelihood estimation procedure is developed for multidimensional scaling of dissimilarity data measured on rating scales. The procedure can fit the euclidian distance model to the data under various assumptions about category widths and under two distributional assumptions. The scoring algorithm for parameter estimation has been developed and implemented in the form of a computer program. Practical uses of the method are demonstrated with an emphasis on various advantages of the method as a statistical procedure.The research reported here was partly supported by Grant A6394 to the author by Natural Sciences and Engineering Research Council of Canada. Portions of this research were presented at the Psychometric Society meeting in Uppsala, Sweden, in June, 1978. MAXSCAL-2.1, a program to perform the computations discussed in this paper may be obtained from the author. Thanks are due to Jim Ramsay for his helpful comments.     

Solutions to some nonlinear equations from nonmetric data

A method is presented to provide estimates of parameters of specified nonlinear equations from ordinal data generated from a crossed design. The analytic method, NOPE, is an iterative method in which monotone regression and the Gauss-Newton method of least squares are applied alternatively until a measure of stress is minimized. Examples of solutions from artificial data are presented together with examples of applications of the method to experimental results.This work was begun while the author was on sabbatical leave during 1970–71 at the Department of Mathematical Psychology, University of Nijmegen, the Netherlands, where discussions with E. E. Roskam on the problem were very helpful. Support was provided by Grant A0151 from the Natural Sciences and Engineering Council, Canada.     

Epistemic logicism & Russell's regressive method

Work on this paper began while I was a Visiting Fellow at the University of Pittsburgh's Center for Philosophy of Science and continued later at the University of Toronto. During this time, financial support was gratefully received from the Social Sciences and Humanities Research Council of Canada.     

Taxicab Correspondence Analysis

Taxicab correspondence analysis is based on the taxicab singular value decomposition of a contingency table, and it shares some similar properties with correspondence analysis. It is more robust than the ordinary correspondence analysis, because it gives uniform weights to all the points. The visual map constructed by taxicab correspondence analysis has a larger sweep and clearer perspective than the map obtained by correspondence analysis. Two examples are provided. This research was financed by the Natural Sciences and Engineering Research Council of Canada. The author thanks Serge Vienneau for his help regarding the graphical displays, and also thanks the editor, associate editor, and two reviewers for their constructive comments.     

Maximum likelihood additivity analysis

A maximum likelihood estimation procedure was developed to fit unweighted and weighted additive models to conjoint data obtained by the categorical rating, the pair comparison or the directional ranking method. The scoring algorithm used to fit the models was found to be both reliable and efficient, and the program MAXADD is capable of handling up to 300 parameters to be estimated. Practical uses of the procedure are reported to demonstrate various advantages of the procedure as a statistical method.The research reported here was supported by Grant A6394 to the author from the Natural Sciences and Engineering Research Council of Canada. Portions of this research were presented at the Psychometric Society meeting in Iowa City, Iowa, in May, 1980.Thanks are due to Jim Ramsay, Justine Sergent and anonymous reviewers for their helpful comments.Two MAXADD programs which perform the computations discussed in this paper may be obtained from the author.     

Regularized Partial and/or Constrained Redundancy Analysis

Methods of incorporating a ridge type of regularization into partial redundancy analysis (PRA), constrained redundancy analysis (CRA), and partial and constrained redundancy analysis (PCRA) were discussed. The usefulness of ridge estimation in reducing mean square error (MSE) has been recognized in multiple regression analysis for some time, especially when predictor variables are nearly collinear, and the ordinary least squares estimator is poorly determined. The ridge estimation method was extended to PRA, CRA, and PCRA, where the reduced rank ridge estimates of regression coefficients were obtained by minimizing the ridge least squares criterion. It was shown that in all cases they could be obtained in closed form for a fixed value of ridge parameter. An optimal value of the ridge parameter is found by G-fold cross validation. Illustrative examples were given to demonstrate the usefulness of the method in practical data analysis situations. We thank Jim Ramsay for his insightful comments on an earlier draft of this paper. The work reported in this paper is supported by Grants 10630 from the Natural Sciences and Engineering Research Council of Canada to the first author.     

On the relationship between item response theory and factor analysis of discretized variables

Equivalence of marginal likelihood of the two-parameter normal ogive model in item response theory (IRT) and factor analysis of dichotomized variables (FA) was formally proved. The basic result on the dichotomous variables was extended to multicategory cases, both ordered and unordered categorical data. Pair comparison data arising from multiple-judgment sampling were discussed as a special case of the unordered categorical data. A taxonomy of data for the IRT and FA models was also attempted.The work reported in this paper has been supported by Grant A6394 to the first author from the Natural Sciences and Engineering Research Council of Canada.     

Matfit: A fortran subroutine for comparing two matrices in a subspace

This research was supported by grant APA 3020 from the Natural Sciences and Engineering Research Council of Canada. The author would like to thank Dr. David O'Hare for providing the data used to illustrate the use of the program MATFIT.     

Monoidal categories with natural numbers object

The notion of a natural numbers object in a monoidal category is defined and it is shown that the theory of primitive recursive functions can be developed. This is done by considering the category of cocommutative comonoids which is cartesian, and where the theory of natural numbers objects is well developed. A number of examples illustrate the usefulness of the concept.This work was partially carried out while both authors were guests of McGill University and while the second author was a guest of Dalhousie University. Both authors acknowledge support from the Natural Sciences and Engineering Research Council of Canada and the Québec Department of Education.     

Maximum marginal likelihood estimation for semiparametric item analysis

The item characteristic curve (ICC), defining the relation between ability and the probability of choosing a particular option for a test item, can be estimated by using polynomial regression splines. These provide a more flexible family of functions than is given by the three-parameter logistic family. The estimation of spline ICCs is described by maximizing the marginal likelihood formed by integrating ability over a beta prior distribution. Some simulation results compare this approach with the joint estimation of ability and item parameters.IRCAMThe research reported in this paper was supported by Grants APA320 and A4035 from the Natural Sciences and Engineering Research Council of Canada. It was also supported by Contract No. F41689-82-C-10020 from the Air Force Human Resources Laboratory to Educational Testing Service. The author wishes to thank M. Abrahamowicz for his assistance and R. Darrell Bock for providing the parameters for the items used in the simulations.     

Laterality differences and shifts as a function of tactile temporal pattern complexity: Implications for differential processing strategies of the cerebral hemispheres

Summary The ability of subjects with a right-hand or left-hand preference to report accurately the number of tactile pulses in temporal sequences presented to preferred and nonpreferred hands was investigated as a function of temporal pattern complexity which varied in terms of intrinsic temporal relations among successive pulses and ranged from slow regular (periodic) sequences of small numbers of pulses to fast irregular (aperiodic) sequences of large numbers of pulses. As the complexity of the pattern increased in terms of pulse number, presentation rate, pulse density, and pulse aperiodicity, all subjects, for both preferred- and nonpreferred-hand stimulation, were increasingly less accurate in reporting the number of pulses in a temporal pattern. Most interesting was the finding that although hand-preference groups did not differ reliably in overall report accuracy, both groups showed a consistent shift in report accuracy from preferred- to nonpreferred-hand stimulation when patterns had more than seven pulses; furthermore, these shifts occurred for all presentation rates and pulse periodicities. A possible relationship between hand preference and cerebral psychological organization is suggested and the data are discussed in terms of the laterality differences reflecting basic underlying cerebral asymmetries in stimulus processing.These investigations were supported by Grant A8621 from the National Research Council of Canada. This paper was prepared while the author was a Visiting Researcher at the Department of Psychology, University of Stockholm, and supported, in part, by a Leave Fellowship awarded by the Social Sciences and Humanities Research Council of Canada. I would like to thank Gordon Tanne for his assistance in data collection and analysis. Requests for offprints should be sent to E.C. Lechelt, Department of Psychology, University of Alberta, Edmonton, Alberta, Canada T6G 2E9.     

A faithful embedding of parallel computations in star-finite models

The purpose of this paper is to show that there exist star-finite tree-structured sets in which the computations of parallel programs can be faithfully embedded, and that the theory of star-finite sets and relations therefore provides a new tool for the analysis of non-deterministic computations.This research was carried out while the author held a Postdoctoral Fellowship from the Natural Sciences and Engineering Research Council of Canada. The author also gratefully acknowledges the support of the Centre inter-universitaire en études catégoriques de Montréal.     

The Perfectionism Cognitions Inventory: Psychometric Properties and Associations with Distress and Deficits in Cognitive Self-management

Two studies were conducted to examine the psychometric properties and correlates of the Perfectionism Cognitions Inventory (PCI) when administered to clinical samples. The PCI is a 25-item measure of automatic thoughts with themes involving perfectionism and beliefs that perfection should be attained. Analyses indicated that the PCI is unidimensional and it has adequate internal consistency. Correlational analyses confirmed that the PCI is associated with psychological distress and deficits in cognitive self-management, including lack of self-reinforcement, lack of a positive self-focus, and perfectionistic inflexibility. Moreover, tests of incremental validity revealed that the PCI accounts for unique variance in levels of anxiety and depression symptoms after removing variance attributable to trait perfectionism dimensions. Overall, the findings suggest that automatic thoughts involving perfectionistic themes can be assessed in a reliable and valid manner in clinical samples. Moreover, it is important to assess perfectionism cognitions as a supplement to trait perfectionism measures when evaluating the role of perfectionism in psychological distress and associated deficits in cognitive self-control. This research was supported by major research grants from Health Canada and the Social Sciences and Humanities Research Council (SSHRC) of Canada to the first two authors, and a Canada Research Chair in Personality & Health awarded to the first author. The fourth author, Thomas Martin, is now deceased and this paper is dedicated to his memory.     

A similarity-based smoothing approach to nondimensional item analysis

The probability that an examinee chooses a particular option within an item is estimated by averaging over the responses to that item of examinees with similar response patterns for the whole test. The approach does not presume any latent variable structure or any dimensionality. But simulated and actual data analyses are presented to show that when the responses are determined by a latent ability variable, this similarity-based smoothing procedure can reveal the dimensionality of ability very satisfactorily.The author wishes to acknowledge the support of the Natural Sciences and Engineering Research Council of Canada through grant A320, and to thank Educational Testing Service for making the data on the Advanced Placement Chemistry Exam available.     

A dual scaling analysis for paired compositions

A paired composition is a response (upon a dependent variable) to the ordered pair <j, k> of stimuli, treatments, etc. The present paper develops an alternative analysis for the paired compositions layout previously treated by Bechtel's [1967] scaling model. The alternative model relaxes the previous one by including row and column scales that provide an expression of bias foreach pair of objects. The parameter estimation and hypothesis testing procedures for this model are illustrated by means of a small group analysis, which represents a new approach to pairwise sociometrics and personality assessment.This study was supported by Grant Nos. MH 12972, MH 10822, and MH 15506 from the National Institute of Mental Health, U. S. Public Health Service. Computing assistance was obtained from the Health Sciences Computing Facility, UCLA, sponsored by N.I.H. special research resources Grant RR-3.The motivation of this effort has been enhanced by Gerald Patterson and his associates, who have kindly provided the illustrative data at the end of the paper. The author would also like to express his appreciation to Wei-Ching Chang of the Oregon Research Institute and the University of Oregon for his substantive contributions to the paper, and to William Chaplin and Mark Layman of the Oregon Research Institute for the programming of the data analytic method. FORTRAN IV program listings for this analysis are available upon request to the author.     

An Extension of Multiple Correspondence Analysis for Identifying Heterogeneous Subgroups of Respondents

An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents’ preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables while the latter is used for identifying relatively homogeneous clusters of respondents. The proposed method offers an integrated graphical display that provides information on cluster-based structures inherent in multivariate categorical data as well as the interdependencies among the data. An empirical application is presented which demonstrates the usefulness of the proposed method and how it compares to several extant approaches. The work reported in this paper was supported by Grant 290439 and Grant A6394 from the Natural Sciences and Engineering Research Council of Canada to the first and third authors, respectively. We wish to thank Ulf B?ckenholt, Paul Green, and Marc Tomiuk for their insightful comments on an earlier version of this paper. We also wish to thank Byunghwa Yang for generously providing us with his data.     

Must a hermeneutical psychoanalysis exclude science?

The work on this article was made possible in part by a grant to all three authors from the Social Sciences and Humanities Research Council of Canada (410-91-0422) and a St. Paul University research award. All three authors contributed equally to the text. An earlier version of this article was presented at the Division of Psychoanalysis of the American Psychological Association annual meeting, August 1990. We are grateful to James Pambrun, Ph.D., Ted O'Grady, and Bertram P. Karon, Ph.D. for their advice and encouragement. Correspondence concerning this article should be addressed to Paul Rigby, St. Paul University, 223 Main St. E., Ottawa, Ont, Canada K1S 1C4.