Extending exploratory diagnostic classification models: Inferring the effect of covariates

Diagnostic models provide a statistical framework for designing formative assessments by classifying student knowledge profiles according to a collection of fine-grained attributes. The context and ecosystem in which students learn may play an important role in skill mastery, and it is therefore important to develop methods for incorporating student covariates into diagnostic models. Including covariates may provide researchers and practitioners with the ability to evaluate novel interventions or understand the role of background knowledge in attribute mastery. Existing research is designed to include covariates in confirmatory diagnostic models, which are also known as restricted latent class models. We propose new methods for including covariates in exploratory RLCMs that jointly infer the latent structure and evaluate the role of covariates on performance and skill mastery. We present a novel Bayesian formulation and report a Markov chain Monte Carlo algorithm using a Metropolis-within-Gibbs algorithm for approximating the model parameter posterior distribution. We report Monte Carlo simulation evidence regarding the accuracy of our new methods and present results from an application that examines the role of student background knowledge on the mastery of a probability data set.     

Exploring the set-theoretical structure of objects by additive trees

Arrangements of feature sets that have been proposed to represent qualitative and quantitative variation among objects are shown to generate identical sets of set-symmetric distances. The set-symmetric distances for these feature arrangements can be represented by path lengths in an additive linear tree. Imperfect versions of these feature arrangements are proposed, which also are indistinguishable by the set-symmetric distance model. The distances for the imperfect versions can be represented by path lengths in an additive imperfectly linear tree. When dissimilarities are defined by the more general contrast model and a constant may be added to proximity data, then for both the perfect and imperfect arrangements an additive tree analysis obtains a perfect fit with an imperfectly linear tree. However, in the case of the contrast model also the distinction between the perfect and imperfect arrangements disappears in that also for the perfect arrangements the resulting tree need no longer be linear.The author is grateful to Mathieu Koppen for detailed comments on an earlier version of this article.     

The Question of God in an Age of Science: Constructions of Reality and Ultimate Reality in Theology and Science

Both science and theology have lately faced a crisis of authority. Their shared realization of the extent to which knowledge is underdetermined by the data and socially constructed provides a kind of common ground for reconsideration of their respective methods of inquiry as well as of the status of the claims they have warrant to make. Both fields are now consciously and critically employing a models approach. This article proposes criteria for assessing models and applies the criteria to one model from each field. The model of understanding evolution as a struggle for existence is considered from the field of science, and the traditional model for understanding the God-world relation as that of a king's relation to his kingdom is considered from the field of theology. Each of these models is evaluated with respect to its credibility, religious viability, and moral adequacy. In each case an alternative analogy is proposed and argued for.     

DIE MARXISMUS – DEBATTE IM “SILBERNEN ZEITALTER”

Im Anfang des 20.Jahrhunderts unterzog eine Reihe von jungen, später berühmt gewordenen Philosophen den Marxismus einer tiefen Kritik. Ihnen ist es gelungen, wichtige Defekte der revolutionären Doktrinen aufzudecken und ihre verhängnivsollen Konsequenzen vorwegzunehmen. Diese Kritik ist auch für die gegenwärtige geistig-politische Situation aktuell.     

Application of the bootstrap methods in factor analysis

A Monte Carlo experiment is conducted to investigate the performance of the bootstrap methods in normal theory maximum likelihood factor analysis both when the distributional assumption is satisfied and unsatisfied. The parameters and their functions of interest include unrotated loadings, analytically rotated loadings, and unique variances. The results reveal that (a) bootstrap bias estimation performs sometimes poorly for factor loadings and nonstandardized unique variances; (b) bootstrap variance estimation performs well even when the distributional assumption is violated; (c) bootstrap confidence intervals based on the Studentized statistics are recommended; (d) if structural hypothesis about the population covariance matrix is taken into account then the bootstrap distribution of the normal theory likelihood ratio test statistic is close to the corresponding sampling distribution with slightly heavier right tail.This study was carried out in part under the ISM cooperative research program (91-ISM · CRP-85, 92-ISM · CRP-102). The authors would like to thank the editor and three reviewers for their helpful comments and suggestions which improved the quality of this paper considerably.     

'The Rich Squander Money by the Thousands'

Following the publication of an unknown letter of Jung's on the theme of the possibility of liberal dictatorship, the authors have presented the actual letter that prompted Jung's reply and a further letter from the 16–year-old boy in Kansas. An interview with Jung in Hearst's International Cosmopolitan Magazine conducted by H.R. Knickerbocker in 1938 initially prompted the boy to write to Jung and the interview, which has been published, is summarized. Economic and financial themes were prominent in the boy's mind and links are made to earlier discussions in this Journal about these matters.