Bayesian adaptive estimation: The next dimension

We propose a new psychometric model for two-dimensional stimuli, such as color differences, based on parameterizing the threshold of a one-dimensional psychometric function as an ellipse. The Ψ Bayesian adaptive estimation method applied to this model yields trials that vary in multiple stimulus dimensions simultaneously. Simulations indicate that this new procedure can be much more efficient than the more conventional procedure of estimating the psychometric function on one-dimensional lines independently, requiring only one-fourth or less the number of trials for equivalent performance in typical situations. In a real psychophysical experiment with a yes-no task, as few as 22 trials per estimated threshold ellipse were enough to consistently demonstrate certain color appearance phenomena. We discuss the practical implications of the multidimensional adaptation. In order to make the application of the model practical, we present two significantly faster algorithms for running the Ψ method: a discretized algorithm utilizing the Fast Fourier Transform for better scaling with the sampling rates and a Monte Carlo particle filter algorithm that should be able to scale into even more dimensions.     

To Weight or Not to Weight? Balancing Influence of Initial Items in Adaptive Testing

It has been widely reported that in computerized adaptive testing some examinees may get much lower scores than they would normally if an alternative paper-and-pencil version were given. The main purpose of this investigation is to quantitatively reveal the cause for the underestimation phenomenon. The logistic models, including the 1PL, 2PL, and 3PL models, are used to demonstrate our assertions. Our analytical derivation shows that, under the maximum information item selection strategy, if an examinee failed a few items at the beginning of the test, easy but more discriminating items are likely to be administered. Such items are ineffective to move the estimate close to the true θ, unless the test is sufficiently long or a variable-length test is used. Our results also indicate that a certain weighting mechanism is necessary to make the algorithm rely less on the items administered at the beginning of the test. This research was partially supported by the NSF Grants SES0241020 and SES0613025. The authors thank the Editor, Associate Editor and two anonymous reviewers for their comments and suggestions. Send further information to Hua-Hua Chang, Department of Psychology, 603 E. Daniel Street, M/C 716, Champaign, IL 61820.     

The hero, the anima and the claustrum: anality and idealization

Joe Redfearn's (1979) classic paper 'The captive, the treasure, the hero and the anal stage of development' is recognized as seminal to the development of Jungian thought about anality, particularly its integration with mainstream (Freudian, Kleinian) psychoanalytic perspectives. This paper develops such an approach through drawing on contributions from Meltzer, Green, Bion, Chasseguet-Smirgel and Kernberg. More specifically, it is argued that over-investment in hero and anima archetypal configurations may represent an attempt to replace the resource of the internal parental couple that, at the level of unconscious phantasy, has been destroyed by the aggrieved child's attack on the primal scene. Unless this usually dissociated sadism can be integrated, the creative epistemophilic instinct may remain blunted, giving rise, through projective identification, to the adoption of a pseudo-adult identity based on appropriation or assertion. This in turn may lead to manic attempts to reach authentic ('animating') experience through the (often erotized) excitement of heroic endeavour. Consideration of both Redfearn's and the author's own clinical material demonstrates how close attention to process as well as content is fundamental to revealing and addressing such likely-to-be dissociated scenarios.     

Factor analysis for clustered observations

Classical factor analysis assumes a random sample of vectors of observations. For clustered vectors of observations, such as data for students from colleges, or individuals within households, it may be necessary to consider different within-group and between-group factor structures. Such a two-level model for factor analysis is defined, and formulas for a scoring algorithm for estimation with this model are derived. A simple noniterative method based on a decomposition of the total sums of squares and crossproducts is discussed. This method provides a suitable starting solution for the iterative algorithm, but it is also a very good approximation to the maximum likelihood solution. Extensions for higher levels of nesting are indicated. With judicious application of quasi-Newton methods, the amount of computation involved in the scoring algorithm is moderate even for complex problems; in particular, no inversion of matrices with large dimensions is involved. The methods are illustrated on two examples.Suggestions and corrections of three anonymous referees and of an Associate Editor are acknowledged. Discussions with Bob Jennrich on computational aspects were very helpful. Most of research leading to this paper was carried out while the first author was a visiting associate professor at the University of California, Los Angeles.     

Building an identifiable latent class model with covariate effects on underlying and measured variables

In recent years, latent class models have proven useful for analyzing relationships between measured multiple indicators and covariates of interest. Such models summarize shared features of the multiple indicators as an underlying categorical variable, and the indicators' substantive associations with predictors are built directly and indirectly in unique model parameters. In this paper, we provide a detailed study on the theory and application of building models that allow mediated relationships between primary predictors and latent class membership, but that also allow direct effects of secondary covariates on the indicators themselves. Theory for model identification is developed. We detail an Expectation-Maximization algorithm for parameter estimation, standard error calculation, and convergent properties. Comparison of the proposed model with models underlying existing latent class modeling software is provided. A detailed analysis of how visual impairments affect older persons' functioning requiring distance vision is used for illustration.This work was supported by National Institute on Aging (NIA) Program Project P01-AG-10184-03 and National Institutes of Mental Health grant R01-MH-56639-01A1. Dr. Bandeen-Roche is a Brookdale National Fellow. The authors wish to thank Drs. Gary Rubin and Sheila West for kindly making the Salisbury Eye Evaluation data available. We also thank the Editor, the Associate Editor, and three referees for their valuable comments.     

On Learnability of Restricted Classes of Categorial Grammars

In this paper we present learning algorithms for classes of categorial grammars restricted by negative constraints. We modify learning functions of Kanazawa [10] and apply them to these classes of grammars. We also prove the learnability of intersection of the class of minimal grammars with the class of k-valued grammars. Presented by Wojciech Buszkowski     

Are waves of relational assumptions eroding traditional analysis?

The author designates as ‘traditional’ those elements of psychoanalytic presumption and practice that have, in the wake of Fordham's legacy, helped to inform analytical psychology and expand our capacity to integrate the shadow. It is argued that this element of the broad spectrum of Jungian practice is in danger of erosion by the underlying assumptions of the relational approach, which is fast becoming the new establishment. If the maps of the traditional landscape of symbolic reference (primal scene, Oedipus et al.) are disregarded, analysts are left with only their own self‐appointed authority with which to orientate themselves. This self‐centric epistemological basis of the relationalists leads to a revision of ‘analytic attitude’ that may be therapeutic but is not essentially analytic. This theme is linked to the perennial challenge of balancing differentiation and merger and traced back, through Chasseguet‐Smirgel, to its roots in Genesis. An endeavour is made to illustrate this within the Journal convention of clinically based discussion through a commentary on Colman's (2013) avowedly relational treatment of the case material presented in his recent Journal paper ‘Reflections on knowledge and experience’ and through an assessment of Jessica Benjamin's (2004) relational critique of Ron Britton's (1989) transference embodied approach.     

医疗情感计算应用的多维困境及其法治实现

情感计算技术依托算法的数据处理能力和自主学习能力已经在医疗健康领域有所实践。但由于医疗领域的特殊性,情感计算技术医疗应用过程中存在着道德合理性风险、规制盲区以及技术羁绊等多重隐患,亟须法律规制。首先,应当坚守“拟主体”身份的道德底线,追求伦理与法治的最佳耦合;其次,应构建权责明晰的算法责任嵌入机制,建立多元协同的算法权力治理机制;最后,应建立健全医疗情感计算技术审查机制,完善情感计算算法风险等级治理体系。