Factor invariance of the Millon Clinical Multiaxial Inventory

Several factor analyses of the Millon Clinical Multiaxial Inventory (MCMI) have resulted in very similar solutions. Interpretation of this consistency is hampered by the fact that the 20 scales of the inventory share items. Overlapping items cause the scales to be linearly dependent and may create structure in the interscale correlation matrix which is separate from the subject response patterns. A factor analysis was performed on the matrix of item-overlap coefficients which describes the underlying artifactual structure of the instrument. Data from two new subject samples were factor analyzed and compared to previously published studies. Similarity coefficients among factors across studies were calculated.     

Daily stress and anxiety and their relation to daily fluctuations of symptoms in asthma and chronic obstructive pulmonary disease (COPD) patients

Although stress and anxiety have long been assumed to play an exacerbatory role in asthma, no study has systematically documented that daily exacerbations of asthma symptoms are related to stress and/or anxiety. In this study, 24 airways obstruction patients (12 asthmatics and 12 chronic obstructive pulmonary disease patients) were instructed to monitor the severity of daily respiratory symptoms. In addition, subjects recorded their daily anxiety level and the number and perceived impact of daily stressors. The results showed that although there were differences between high- and low-stress days for both groups, there were no differences between groups on symptom severity or between high- and low-anxiety days, as measured by the State-Trait Anxiety Inventory (STAI). Thus, although the number and impact of daily stressors were found to be directly associated with the severity of asthma symptoms, anxiety does not appear to have a direct role in the exacerbation of asthma. The findings failed to support the anxiety theory of asthma but provided an explanation for the poor results obtained in previous treatment studies which employed anxiety management with asthmatics.     

Factor structure of the Treatment Evaluation Inventory: Implications for measurement of treatment acceptability

The Treatment Evaluation Inventory (TEI), a frequently used measure of treatment acceptability, was used by 164 undergraduates to rate the acceptability of each of the following treatments: differential reinforcement of other behavior, exclusionary time-out, overcorrection, medical restraint, contingent electric shock, and physical restraint. TEI ratings of each treatment type were grouped separately, variance-covariance matrices were formed and compared, and data were subjected to factor analysis. The results indicated that the factor structure of the TEI varied with the treatment it was used to evaluate. Item analysis of the TEI indicated a high degree of internal consistency, although item-total correlations varied between rated treatments. The findings suggest that although the TEI is a reliable instrument, sensitive assessment of the treatment acceptability construct probably requires multidimensional measurement.     

Aristotle and the tradition of rhetorical argumentation

The first part of this paper contends that argumentation is central and essential to Aristotle's Rhetoric, and recounts a number of arguments in support of that view, particularly the recognition that deliberative rhetoric or the rhetoric of counsel is the primary concern of Aristotle's work. The second part of the paper reviews the work that follows in this present volume to show that the other writers' views fit in perfectly with this thesis.     

A quasi-nonmetric method for multidimensional scaling VIA an extended euclidean model

An Extended Two-Way Euclidean Multidimensional Scaling (MDS) model which assumes both common and specific dimensions is described and contrasted with the standard (Two-Way) MDS model. In this Extended Two-Way Euclidean model then stimuli (or other objects) are assumed to be characterized by coordinates onR common dimensions. In addition each stimulus is assumed to have a dimension (or dimensions) specific to it alone. The overall distance between objecti and objectj then is defined as the square root of the ordinary squared Euclidean distance plus terms denoting the specificity of each object. The specificity,s _j , can be thought of as the sum of squares of coordinates on those dimensions specific to objecti, all of which have nonzero coordinatesonly for objecti. (In practice, we may think of there being just one such specific dimension for each object, as this situation is mathematically indistinguishable from the case in which there are more than one.)We further assume that _ij =F(d _ij ) +e _ij where _ij is the proximity value (e.g., similarity or dissimilarity) of objectsi andj,d _ij is the extended Euclidean distance defined above, whilee _ij is an error term assumed i.i.d.N(0, ²).F is assumed either a linear function (in the metric case) or a monotone spline of specified form (in the quasi-nonmetric case). A numerical procedure alternating a modified Newton-Raphson algorithm with an algorithm for fitting an optimal monotone spline (or linear function) is used to secure maximum likelihood estimates of the paramstatistics) can be used to test hypotheses about the number of common dimensions, and/or the existence of specific (in addition toR common) dimensions.This approach is illustrated with applications to both artificial data and real data on judged similarity of nations.     

Incorporating prior theory in covariance structure analysis: A bayesian approach

A Bayesian approach to the testing of competing covariance structures is developed. The method provides approximate posterior probablities for each model under consideration without prior specification of individual parameter distributions. The method is based on ayesian updating using cross-validated pseudo-likelihoods. Given that the observed variables are the samefor all competing models, the approximate posterior probabilities may be obtained easily from the chi square values and other known constants, using only a hand calculator. The approach is illustrated using and example which illustrates how the prior probabilities can alter the results concerning which model specification is preferred.     

TOWARD A NEW RELATION BETWEEN HUMANITY AND NATURE: RECONSTRUCTING T'IEN-JEN-HO-I

Abstract. The traditional Chinese idea of t'ien-jen-ho-i (Heaven and humanity in union) implies that humanity has to live in harmony with nature. As science and technology progress, however, the idea appears increasingly outmoded, and it becomes fashionable to talk about overcoming nature. Ironically, though, the further science reaches the more clearly are its limitations exposed. The exploitation of nature not only endangers many life forms on earth but threatens the very existence of the human species. I propose that a reconstruction of the traditional Chinese idea of T'ien-jen-ho-i will help us envisage a new and salutary relation between humanity and nature.     

The pathological left-handedness syndrome

A clinical syndrome of pathological left-handedness (PLH) is proposed to identify the pattern of correlative changes in lateral development associated with early brain injury in some manifest left-handers. This syndrome is believed to be caused by a hemispheric lesion that is predominantly left-sided (or bilateral asymmetric), which onsets before Age 6, and which encroaches upon the critical speech zones of the frontotemporal/frontoparietal cortex. The pattern of changes may include any or all of the following features: shifts in manual dominance, trophic changes in the extremities, transfer of hemispheric speech, and/or intrahemispheric reorganization of visuospatial cognitive functions. Although some of these correlates of PLH have long been known, they have not been recognized as an interrelated pattern of traits that constitute a clinical syndrome. Identification of these individuals, all manifest left-handers, will be shown to have implications for diagnosis/remediation and for models of recovery of function.     

Nonconvergence,improper solutions,and starting values in lisrel maximum likelihood estimation

In the framework of a robustness study on maximum likelihood estimation with LISREL three types of problems are dealt with: nonconvergence, improper solutions, and choice of starting values. The purpose of the paper is to illustrate why and to what extent these problems are of importance for users of LISREL. The ways in which these issues may affect the design and conclusions of robustness research is also discussed.     

Statistical consistency and hypothesis testing for nonmetric multidimensional scaling

The properties of nonmetric multidimensional scaling (NMDS) are explored by specifying statistical models, proving statistical consistency, and developing hypothesis testing procedures. Statistical models with errors in the dependent and independent variables are described for quantitative and qualitative data. For these models, statistical consistency often depends crucially upon how error enters the model and how data are collected and summarized (e.g., by means, medians, or rank statistics). A maximum likelihood estimator for NMDS is developed, and its relationship to the standard Shepard-Kruskal estimation method is described. This maximum likelihood framework is used to develop a method for testing the overall fit of the model.