Separating The Effects Of Trial-specific And Average Sample-stimulus Duration In Delayed Matching To Sample In Pigeons

Pigeons were studied in two experiments employing delayed matching-to-sample (DMTS) tasks in which the reduction in delay to reinforcement signaled by the onset of the sample stimulus was manipulated by varying sample-stimulus duration. In Experiment 1, the duration of the sample stimulus was either 5 s or 10 s for one sample stimulus and 10 s or 20 s for the other. Subjects matched more frequently when the sample duration was 10 s following the sample associated with the shorter average duration. This finding is analogous to the memory distribution effect found by Honig (1987) in a successive DMTS task that varied retention interval. In Experiment 2, sample duration was either 5 s or 15 s. In Phases 1 and 3 each sample duration was correlated with a particular sample color, and in Phase 2 sample duration and color were uncorrelated. When sample duration was 5 s, subjects matched more frequently when sample duration and color were correlated than when they were uncorrelated. Overall, subjects matched more frequently when sample duration and color were correlated. The data from both experiments support Wixted's (1989) model, which states that one determinant of choice in a DMTS task is the delay-reduction value of the sample stimulus.     

General estimators for the reliability of qualitative data

We study a proportional reduction in loss (PRL) measure for the reliability of categorical data and consider the general case in which each ofN judges assigns a subject to one ofK categories. This measure has been shown to be equivalent to a measure proposed by Perreault and Leigh for a special case when there are two equally competent judges, and the correct category has a uniform prior distribution. We consider a general framework where the correct category is assumed to have an arbitrary prior distribution, and where classification probabilities vary by correct category, judge, and category of classification. In this setting, we consider PRL reliability measures based on two estimators of the correct category—the empirical Bayes estimator and an estimator based on the judges' consensus choice. We also discuss four important special cases of the general model and study several types of lower bounds for PRL reliability.Bruce Cooil is Associate Professor of Statistics, and Roland T. Rust is Professor and area head for Marketing, Owen Graduate School of Management, Vanderbilt University. The authors thank three anonymous reviewers and an Associate Editor for their helpful comments and suggestions. This work was supported in part by the Dean's Fund for Faculty Research of the Owen Graduate School of Management, Vanderbilt University.     

Concerning the integration of sciences: Kinds and stages

The detailed analysis allows to discern seven kinds of integration, namely: I₁ consisting in the synthesis of scientific disciplines from their elements, including disciplinary unification I₁; I₂ inclusion of a science in (reduction to) another, more general; I₃ — links between different sciences, especially establishing of common elements; I₄ — interdisciplines bridging various sciences; I₅ — combination of two (or more) disciplines into a new (complex) science; I₆ — a general approach to several domains or multidisciplinary unification; I₇ — transdisciplinary sciences about relations of the same type in various traditional domains. These kinds of integration are interwoven with processes of differentiation, viz. D₁ — internal differentiation of the sciences resulting of I₁; D₂ — interdisciplinary differentiation concomitant I₄, and D₃ — specialization of I₇ sciences in several sections. As a result integration and differentiation are combined in the pairs I₁ — D₁, I₇ — D₃, and D₂ — I₄. The processes of integration (and differentiation) may be presented schematically in the following (not strictly isolated one of another) sequence: in the 17th century started I₁ followed by D₁, and in the last decades by I₁ during the 18th and the 19th c. cases of I₂ and I₃ appear; I₄ (together with D₂) is unfolding since the late 19th century. Finally, I₇ (and D₃), as well as I₅ and I₆ pertain to the latter half of our century. Representative are for one thing I₁, I₄, and I₇ outlining the main stages of integration and at the same time connected with respective kinds of differentiation.     

Uncertainty, entitativity, and group identification

Two studies examined the effects of self-uncertainty and ingroup entitativity on group identification. From uncertainty reduction theory (Hogg, 2000), it was hypothesized that people would identify most strongly with their group if they felt self-conceptually uncertain and the group was highly entitative. Study 1 was a field experiment (N = 114) in which the perceived entitativity of participants’ political party was measured, and self-uncertainty was primed (high vs. low). Study 2 was a laboratory experiment (N = 89) with ad hoc non-interactive groups. Uncertainty was primed as in Study 1, but perceived entitativity was manipulated. In both cases the dependent variable was a multi-item measure of group identification. The hypothesis was fully supported in both studies—participants identified more strongly when they were uncertain and the group was highly entitative. Implications of this research for the role of uncertainty and social identity in extremism, orthodoxy, and ideological belief systems are discussed.     

Causal uncertainty during initial interactions

Causal uncertainty (CU) refers to persistent doubts people have about their ability to understand causes of social events. Although such confusion about social dynamics should affect social exchanges, previous research has been limited to the realm of social cognition (i.e., computer‐based studies exploring perceptions of hypothetical others). In three studies, we explored CU effects during real‐time social interactions with unacquainted conversational partners. We found that high CU participants perceived their conversations and conversational partners more negatively than did low CU participants and that these negative social perceptions stemmed from an inability to sufficiently reduce their cognitive uncertainty. Copyright © 2012 John Wiley & Sons, Ltd.     

用层级相合性指标探测反应数据中噪音大小

不同的认知诊断模型（CDM）对反应数据中噪音的抗干扰能力不同,在评估CDM性能的模拟实验中,反应数据中所含噪音的大小是十分重要的实验条件。由于噪音的内隐性,为应用中选用相应的CDM带来困难。本文在认知模型已知条件下,欲使用MHCI和NHCI指标评估认知诊断测验的反应数据（0, 1评分）中噪音的大小。模拟实验表明,两指标与噪音存在明显的统计规律。尤其是以NHCI为主要自变量对噪音进行预测的回归方程中,回归模型解释率均接近90%;以此实现对噪音的有效预测,从而为选择CDM提供一个参考。     

Guiding drivers towards safer driving speed: Exploiting visual dominance in speed adaptation

Inappropriate speed is a main cause of accidents. Drivers are often unaware of potential risks due to inadequate speed. To prevent dangerous situations, we need to understand perceptual factors influencing human speed perception. Due to the prominent role of vision in driving, we examined the effect of visuo-spatial stimuli on speed based on the optic flow. While developing an adaptive infrastructure measure to reduce speed, we conducted two consecutive studies, a driving simulator study and a field test to investigate findings further. In both studies, we placed lights on two sides of a highway exit and either illuminated them statically or activated them in a way that they appeared to be moving towards the driver. We expected drivers to slow down more when seeing static light stimuli compared to a baseline without lights. We also expected drivers to decrease speed more in conditions with oncoming lights compared to a baseline, and to static lights, due to distorted speed perception. The first study in a static driving simulator revealed no difference between conditions. In the field test, both static lights and lights moving towards the driver led to a speed reduction compared to a baseline but did not differ from one another. Lights in general led to lower driving speed, potentially due to their warning character, but we found no difference between the light conditions, suggesting that the effect might not be based on the optic flow. Future research should investigate the relationship between driven and perceived speed more closely.     

Word informativity influences acoustic duration: Effects of contextual predictability on lexical representation

Language-users reduce words in predictable contexts. Previous research indicates that reduction may be stored in lexical representation if a word is often reduced. Because representation influences production regardless of context, production should be biased by how often each word has been reduced in the speaker’s prior experience. This study investigates whether speakers have a context-independent bias to reduce low-informativity words, which are usually predictable and therefore usually reduced. Content word durations were extracted from the Buckeye and Switchboard speech corpora, and analyzed for probabilistic reduction effects using a language model based on spontaneous speech in the Fisher corpus. The analysis supported the hypothesis: low-informativity words have shorter durations, even when the effects of local contextual predictability, frequency, speech rate, and several other variables are controlled for. Additional models that compared word types against only other words of the same segmental length further supported this conclusion. Words that usually appear in predictable contexts are reduced in all contexts, even those in which they are unpredictable. The result supports representational models in which reduction is stored, and where sufficiently frequent reduction biases later production. The finding provides new evidence that probabilistic reduction interacts with lexical representation.     

An Empirical Investigation of Population Invariance in the Value of Subscores

Recently there has been an increasing level of interest in subtest scores, or subscores, for their potential diagnostic value. Haberman (2008 Haberman, S. J. 2008. When can subscores have value?. Journal of Educational and Behavioral Statistics, 33: 204–229. [Crossref], [Web of Science ®] , [Google Scholar]) suggested a method to determine if a subscore has added value over the total score. Researchers have often been interested in the performance of subgroups—for example, those based on gender or ethnicity—on subtests. Several researchers found that the difference in performance between the gender-based subgroups varied over the different subtests. In this article, we examine whether the added values of the subscores vary between subgroups using data from several operational tests, including an international English proficiency test. For these data sets, the added values of the subscores occasionally vary over the subgroups, but the added values of the augmented subscores are invariant over the subgroups.