Data And Phenomena: A Distinction Reconsidered

Bogen and Woodward (1988) advance adistinction between data and phenomena. Roughly, theformer are the observations reported by experimentalscientists, the latter are objective, stable featuresof the world to which scientists infer based onpatterns in reliable data. While phenomena areexplained by theories, data are not, and so theempirical basis for an inference to a theory consistsin claims about phenomena. McAllister (1997) hasrecently offered a critique of their version of thisdistinction, offering in its place a version on whichphenomena are theory laden, and hence on which theempirical support for inferences to theories is also,unavoidably, theory laden. In this commentary I arguethat McAllister and Bogen and Woodward are mistaken inthinking that the distinction is necessary, and thatthe empirical support for inferences to theories isnot necessarily theory laden in the way McAllister'saccount entails they are.     

Comparing Data Sets: Implicit Summaries of the Statistical Properties of Number Sets

Comparing datasets, that is, sets of numbers in context, is a critical skill in higher order cognition. Although much is known about how people compare single numbers, little is known about how number sets are represented and compared. We investigated how subjects compared datasets that varied in their statistical properties, including ratio of means, coefficient of variation, and number of observations, by measuring eye fixations, accuracy, and confidence when assessing differences between number sets. Results indicated that participants implicitly create and compare approximate summary values that include information about mean and variance, with no evidence of explicit calculation. Accuracy and confidence increased, while the number of fixations decreased as sets became more distinct (i.e., as mean ratios increase and variance decreases), demonstrating that the statistical properties of datasets were highly related to comparisons. The discussion includes a model proposing how reasoners summarize and compare datasets within the architecture for approximate number representation.     

Correlational Structure of the MCMI-III Personality Disorder Scales and Comparisons With Other Data Sets

We examine the correlational structure of the personality disorder (PD) scales from the MCMI-III (Millon, 1994) among 614 college students. The correlation matrix from our nonclinical sample was highly similar to the clinical sample matrices reported by Millon (1994). Further analyses revealed that the correlation matrices from a variety of MCMI data sets are generally similar to one another, but are only moderately similar to PD correlation matrices based on other assessment techniques. PD correlation matrices based on different assessment techniques are generally not very similar to one another. Two-, 3-, and 4-factor solutions for the MCMI-III PD scales are reported and provide a framework for integrating apparently conflicting findings from previous work. The 4-factor solution was most meaningful and was consistent with the 5-factor model of PD.     

Modeling Cyclical Patterns in Daily College Drinking Data with Many Zeroes

Daily college drinking data often have highly skewed distributions with many zeroes and a rising and falling pattern of use across the week. Alcohol researchers have typically relied on statistical models with dummy variables for either the weekend or all days of the week to handle weekly patterns of use. However, weekend versus weekday categorizations may be too simplistic and saturated dummy variable models too unwieldy, particularly when covariates of weekly patterns are included. In the present study we evaluate the feasibility of cyclical (sine and cosine) covariates in a multilevel hurdle count model for evaluating daily college alcohol use data. Results showed that the cyclical parameterization provided a more parsimonious approach than multiple dummy variables. The number of drinks when drinking had a smoothly rising and falling pattern that was reasonably approximated by cyclical terms, but a saturated set of dummy variables was a better model for the probability of any drinking. Combining cyclical terms and multilevel hurdle models is a useful addition to the data analyst toolkit when modeling longitudinal drinking with high zero counts. However, drinking patterns were not perfectly sinusoidal in the current application, highlighting the need to consider multiple models and carefully evaluate model fit.     

Latent Theme Dictionary Model for Finding Co-occurrent Patterns in Process Data

Psychometrika - Process data, which are temporally ordered sequences of categorical observations, are of recent interest due to its increasing abundance and the desire to extract useful...     

非良基集合的域和分类

本文介绍正则互模拟理论并比较了正则互模拟的外延性大小,通过对非良基公理之间不相容的条件的讨论,我们进一步比较了由正则互模拟决定的非良基集合域的大小,最后对非良基集合论FAFA、SAFA和AFA中的非良基集合进行了分类。     

物理学与特异现象

前言:Gerard t’Hooft是著名荷兰理论物理学家。1999年他和他的老师 Marfinus vtlfman一起,因在建立粒子物理中标准模型的重大贡献,获得本世纪最后一次的诺贝尔物理奖。本文是t’Hooft教授为回答许多询问他如何看待特异现象的问题而写。由于文中提及不少有关理论物理的知识,为便于广大读者阅读,对原文作了适当的删改,但对其主要论点,则全部忠实于原文。     

Basic Phenomena in Learning

Kinsey, A. C., Pomeroy, W. B., &; Martin, C. E. Sexual Behavior in the Human Male. Philadelphia: Saunders, 1948. Pp. 804. Reviewed by Albert Ellis     

Comparison of Alcohol and Other Drug Use Trends Between a Prohibitionist University and National Data Sets

This article provides information on a decade of trends and prevalence of substance use at a Midwestern prohibitionist university. Trends were based on three data collection times, 1995, 2000, and 2005. This information was compared with results of a number of national surveys to identify trends in the data. Total averages for the prohibitionist sample were 42.6% for alcohol use; 18.2% for binge drinking; 35.4% for tobacco use; and 34.1% for marijuana use. With the exception of binge drinking, which remained stable, the gap between substance use rates for the prohibitionist university and the results of national surveys have widened slightly.     

A Nonparametric,Multiple Imputation-Based Method for the Retrospective Integration of Data Sets

Complex research questions often cannot be addressed adequately with a single data set. One sensible alternative to the high cost and effort associated with the creation of large new data sets is to combine existing data sets containing variables related to the constructs of interest. The goal of the present research was to develop a flexible, broadly applicable approach to the integration of disparate data sets that is based on nonparametric multiple imputation and the collection of data from a convenient, de novo calibration sample. We demonstrate proof of concept for the approach by integrating three existing data sets containing items related to the extent of problematic alcohol use and associations with deviant peers. We discuss both necessary conditions for the approach to work well and potential strengths and weaknesses of the method compared to other data set integration approaches.     

Recurrent Phenomena in Group Psychotherapy

The Clown Club is a short term therapeutic group that makes use of structured fantasy and creative drama as the vehicle for the expression and resolution of conflict. In this group, children are invited to create a pretend identity, a clown character which can become a metaphorical expression of themselves. Each child creates a life story, and the group as a whole constructs a tale of how they came together and how they get along interpersonally. This story encompasses all group stages, from its beginning, through the central task of planning and performing a circus show, to its termination.

In this paper we describe the background that led to the development of the Clown Club. Details of how the group is designed and carried out are presented, along with clinical examples and an appraisal of the model at this stage.     

时间相关决策中的非理性现象

时间相关决策中存在着时间成本模糊、时间感知不稳定和远近选择决策权重不稳定等非理性现象。心理账户因素、决策认知因素、决策情境因素和个体因素影响时间相关决策中非理性现象的产生。通过加强时间价值感知训练、理性分析和想象后悔、团队决策、制订合理时间计划和理解社会文化等方法, 可减少时间相关决策中的非理性现象。研究者在未来可关注主观心理时间和高科技对时间相关决策的影响、个体时间相关决策社会化的过程、改变学科视角和实验范式进行研究等。     

科学探索与超自然现象

应中国科普研究所的邀请,国际探索中心(CenterforInquiry,CFI)代表团一行8人(含3位陪同)于2005年4月15日至29日来华进行友好访问和开展学术交流。代表团成员来自美国、加拿大、新西兰等国家,涉及的学科有物理学、心理学、无神论、科技哲学等,代表团成员长期在欧美的大学、社区进行科学理性、科学伦理的普及教育,在媒体上大力提倡科学与无神论,并对一些声称的超自然现象进行科学的调查,对一些打着科学旗号进行欺骗和非法牟利的团体和个人进行揭露和批判。     

Sets and Plural Comprehension

The state of affairs of some things falling under a predicate is supposedly a single entity that collects these things as its constituents. But whether we think of a state of affairs as a fact, a proposition or a possibility, problems will arise if we adopt a plural logic. For plural logic says that any plurality include themselves, so whenever there are some things, the state of affairs of their plural self-inclusion should be a single thing that collects them all. This leads to paradoxes analogous to those that afflict naïve set theory. Here I suggest that they are the very same paradoxes, because sets can be reduced to states of affairs. However, to obtain a consistent theoretical reduction we must restrict the usual axiom scheme of Comprehension for plural logic to ‘stratified’ formulas, to avoid viciously circular definitions. I prove that with this modification to the background plural logic, the theory of states of affairs is consistent; moreover, it yields the axioms of the familiar set theory NFU.     

Vagueness and Blurry Sets

This paper presents a new theory of vagueness, which is designed to retain the virtues of the fuzzy theory, while avoiding the problem of higher-order vagueness. The theory presented here accommodates the idea that for any statement S ₁ to the effect that Bob is bald is x true, for x in [0,1], there should be a further statement S ₂ which tells us how true S ₁ is, and so on – that is, it accommodates higher-order vagueness – without resorting to the claim that the metalanguage in which the semantics of vagueness is presented is itself vague, and without requiring us to abandon the idea that the logic – as opposed to the semantics – of vague discourse is classical. I model the extension of a vague predicate P as a blurry set, this being a function which assigns a degree of membership or degree function to each object o, where a degree function in turn assigns an element of [0,1] to each finite sequence of elements of [0,1]. The idea is that the assignment to the sequence 0.3,0.2, for example, represents the degree to which it is true to say that it is 0.2 true that o is P to degree 0.3. The philosophical merits of my theory are discussed in detail, and the theory is compared with other extensions and generalisations of fuzzy logic in the literature.