应当关注时间心理无意识的研究

随着心理无意识研究在记忆、学习和思维等领域的兴起,内隐时间认知也逐步成为时间心理学中的一个研究热点。本文分析了探究内隐时间认知的四种方法:分离范式、序列学习范式、表征动量范式和计时分布相关范式,指出内隐时间认知实验范式在无意识时间人格与社会心理学中的研究也是有相当前景的。     

Dysfunctional implications of narrow window theory: variability in the intuitive assessment of correlation

Narrow Window theory, suggested by Y. Kareev ten years ago, has so far focused on one central implication of the limited capacity of working memory on intuitive correlation estimation, namely, overestimation of the distal population correlation. This paper points to additional and perhaps more dramatic implications due to the large dispersion of intuitive estimates: (a) large estimation errors, possibly causing overestimation of negligible rhos, misses of strong rhos, and distorted hierarchies of the rhos between different pairs of variables; and (b) large interpersonal differences in the estimation of any given rho and highly incongruent hierarchies of estimated correlations between different pairs of variables. These implications impede both individuals' adaptation to the empirical world and communication among themselves.     

“Primary Relations” In a New Foundational Axiomatic Framework

The new system of axioms we propose is based on the foundational theory of De Giorgi et al. Scuola Normale Superiore di Pisa, Preprints di Matematica 26: 1 (1996) slightly modified. In that paper (which is dedicated to a new axiomatic framework for mathematics, informatics and logic) the authors use two kinds of primitive notions: relations and qualities. Since their system is based on the distribution paradigm, they start from distinction. We propose to shift the perspective and to start from unity and then from within unity to pass to distinction; to this end we apply ideas of Lesniewski, Nijhoff International Philosophy Series 44 (1992). We introduce only one kind of entity as a primitive notion, namely relations, and treat qualities as articulations of relations. The new concept of “primary relation” permits the introduction of a dynamic, non-standard form of identity, which we hope will find application in various fields where self-referential structures are required.     

Is Psychology Based on a Methodological Error?

It is believed a proven fact that variables in social and personality psychology match to normal distribution with its single peak. Multiple peaks are explained by independent variables. However, after a comprehensive data analysis of more than 8.000 patients and on the basis of a bio-psycho-social model with 27 scales, we arrived at the conclusion that normal distribution and the psychometric error theory cannot withstand critical analysis in large samples. Beyond the “truth” that is proved by distribution-dependent statistical inferences, there exists another “truth” that is denied by the empirical doctrine. This “truth” is influenced by compensatory belief systems and explains paradoxes in quality of life research. We hypothesize that items, referred to life risks are micro-stressors, triggering self-regulatory processes as a humanly inherent response, deeply anchored in human evolution. Especially when exposed to threatening experiences, self-focused attention generates amplified multimodal distributions and subverts the methodological premises by an ambivalence-bias between thrill and threat, hopes and fears, pleasure and pain, success and failure, etc. In this article we want to focus attention to the incommensurability between test theoretical axioms and the way people usually respond to self-focused items. We discuss basic distribution patterns and approach to an evolutionary theory of fluctuation of validity.

Computing maximum likelihood estimates of loglinear models from marginal sums with special attention to loglinear item response theory

In this paper algorithms are described for obtaining the maximum likelihood estimates of the parameters in loglinear models. Modified versions of the iterative proportional fitting and Newton-Raphson algorithms are described that work on the minimal sufficient statistics rather than on the usual counts in the full contingency table. This is desirable if the contingency table becomes too large to store. Special attention is given to loglinear IRT models that are used for the analysis of educational and psychological test data. To calculate the necessary expected sufficient statistics and other marginal sums of the table, a method is described that avoids summing large numbers of elementary cell frequencies by writing them out in terms of multiplicative model parameters and applying the distributive law of multiplication over summation. These algorithms are used in the computer program LOGIMO. The modified algorithms are illustrated with simulated data. The author thanks Wim J. van der Linden, Gideon J. Mellenberh and Namburi S. Raju for their valuable comments and suggestions.     

The relationship between Fisher's exact test and Pearson's chi-square test: A bayesian perspective

It is demonstrated in this paper that two major tests for 2 × 2 talbes are highly related from a Bayesian perspective. Although it is well-known that Fisher's exact and Pearson's chi-square tests are asymptotically equivalent, the present analysis shows that a formal similarity also exists in small samples. The key assumption that leads to the resemblance is the presence of a continuous parameter measuring association. In particular, it is shown that Pearson's probability can be obtained by integrating a two-moment approximation to the posterior distribution of the log-odds ratio. Furthermore, Pearson's chi-square test gave an excellent approximation to the actual Bayes probability in all 2×2 tables examined, except for those with extremely disproportionate marginal frequencies.     

Learning about food: starlings, skinner boxes, and earthworms

Despite its importance as a tool for understanding a wide range of animal behavior, the study of reinforcement schedules in the laboratory has suffered from difficulties in the biological interpretation of its findings. This study is an operant-laboratory investigation of the ability of European starlings, Sturnus vulgaris, to learn to respond adaptively to the problem of foraging on patchily distributed prey that are uncertainly located in space. In order to maximize the biological relevance of the laboratory study, variation in the aggregation of earthworms, Lumbricus terrestris (a prey species), was rigorously quantified from the field, and the experimental birds were presented with reinforcement schedules designed to represent the extremes of the observed variation. The results demonstrate that, even for a single prey species, the degree to which individuals are aggregated can vary markedly over a range of spatial scales, and that starlings can rapidly learn to respond, in an adaptive manner, to these variations. These findings suggest that starlings are capable of adjusting their behavior to facilitate the efficient exploitation of prey that occurs in patches of an uncertain nature, and thus illustrate the heuristic value of an ecologically informed operant-laboratory approach to studying foraging behavior.     

Some contributions to efficient statistics in structural models: Specification and estimation of moment structures

Current practice in structural modeling of observed continuous random variables is limited to representation systems for first and second moments (e.g., means and covariances), and to distribution theory based on multivariate normality. In psychometrics the multinormality assumption is often incorrect, so that statistical tests on parameters, or model goodness of fit, will frequently be incorrect as well. It is shown that higher order product moments yield important structural information when the distribution of variables is arbitrary. Structural representations are developed for generalizations of the Bentler-Weeks, Jöreskog-Keesling-Wiley, and factor analytic models. Some asymptotically distribution-free efficient estimators for such arbitrary structural models are developed. Limited information estimators are obtained as well. The special case of elliptical distributions that allow nonzero but equal kurtoses for variables is discussed in some detail. The argument is made that multivariate normal theory for covariance structure models should be abandoned in favor of elliptical theory, which is only slightly more difficult to apply in practice but specializes to the traditional case when normality holds. Many open research areas are described.     

Comparing latent distributions

We consider the problem of comparingm latent population distributions when the observed values are scores on a test battery with binary items. The latent densities are assumed to be normal densities, and we consider a test for equality of the means as well as a test equality of the variances. In addition, we consider a longitudinal model, where the test battery has been applied to the same individuals at different points in time. This model allows for correlations between the latent variable at different time points, and methods are discussed for estimating the correlation coefficient.This work was supported in part by a grant from the Danish Social Science Research Council.     

Overshadowing by fixed- and variable-duration stimuli

Two experiments investigated the effect of the temporal distribution form of a stimulus on its ability to produce an overshadowing effect. The overshadowing stimuli were either of the same duration on every trial, or of a variable duration drawn from an exponential distribution with the same mean duration as that of the fixed stimulus. Both experiments provided evidence that a variable-duration stimulus was less effective than a fixed-duration cue at overshadowing conditioning to a target conditioned stimulus (CS); moreover, this effect was independent of whether the overshadowed CS was fixed or variable. The findings presented here are consistent with the idea that the strength of the association between CS and unconditioned stimulus (US) is, in part, determined by the temporal distribution form of the CS. These results are discussed in terms of time-accumulation and trial-based theories of conditioning and timing.