The approximation of two-mode proximity matrices by sums of order-constrained matrices

A least-squares strategy is proposed for representing a two-mode proximity matrix as an approximate sum of a small number of matrices that satisfy certain simple order constraints on their entries. The primary class of constraints considered define Q-forms (or anti-Q-forms) for a two-mode matrix, where after suitable and separate row and column reorderings, the entries within each row and within each column are nondecreasing (or nonincreasing) to a maximum (or minimum) and thereafter nonincreasing (or nondecreasing). Several other types of order constraints are also mentioned to show how alternative structures can be considered using the same computational strategy.     

The assessment of depression in children: The internal structure of the child depression inventory (CDI)

In the present report three separate studies of childhood depression were conducted. First, the internal structure of the Child Depression Inventory (CDI), with 216 children representing various ethnic groups with equal numbers of boys and girls, was evaluated through a factor analysis and by various internal-reliability measures (e.g. split-half reliabilities, Pearson correlations of each item to the total score). Four factors were established and internal reliability of the scale proved to be high. The relationship of the factor structure of the CDI to Kendell's Type A and B categorization of depression are discussed. In Study 2 the relationship of demographic variables to the CDI using the same group of children described for Study 1 was employed. Evaluating the characteristics of depression across age, sex and so on in children has not been frequently studied, and was deemed appropriate for the present investigation. Age proved to be a significant factor in depression scores although race and gender did not. With respect to age, older children tended to display more symptomatology. Comparisons of depressed children to nondepressed children also showed that age was a factor in the obtained scores, and range of severity in both groups. Depressed children differed from nondepressed children on all 27 items indicating that all the items on the CDI seem to be measuring a unitary concept. Study 3 compared CDI scores to a measure of social behavior, the Matson Evaluation of Social Skills with Youngster (MESSY). Seventy-six children (36 girls and 40 boys), ages 4–10 yrs $\text{(}\text{X}\text{?}\text{= 7)}$ were evaluated. Appropriate Social Skills was negatively correlated with childhood depression, and Inappropriate Impulsive/Assertiveness was positively correlated with depressive features described under the factor Guilt/Irritability. The implications of these data for further research on assessment, differential diagnosis and evaluation of treatment research are discussed.     

The rowwise correlation between two proximity matrices and the partial rowwise correlation

This paper discusses rowwise matrix correlation, based on the weighted sum of correlations between all pairs of corresponding rows of two proximity matrices, which may both be square (symmetric or asymmetric) or rectangular. Using the correlation coefficients usually associated with Pearson, Spearman, and Kendall, three different rowwise test statistics and their normalized coefficients are discussed, and subsequently compared with their nonrowwise alternatives like Mantel'sZ. It is shown that the rowwise matrix correlation coefficient between two matricesX andY is the partial correlation between the entries ofX andY controlled for the nominal variable that has the row objects as categories. Given this fact, partial rowwise correlations (as well as multiple regression extensions in the case of Pearson's approach) can be easily developed.The author wishes to thank the Editor, two referees, Jan van Hooff, and Ruud Derix for their useful comments, and E. J. Dietz for a copy of the algorithm of the Mantel permutation test.     

Analyzing sequential categorical data: Individual variation in markov chains

Markov chains are probabilistic models for sequences of categorical events, with applications throughout scientific psychology. This paper provides a method for anlayzing data consisting of event sequences and covariate observations. It is assumed that each sequence is a Markov process characterized by a distinct transition probability matrix. The objective is to use the covariate data to explain differences between individuals in the transition probability matrices characterizing their sequential data. The elements of the transition probability matrices are written as functions of a vector of latent variables, with variation in the latent variables explained through a multivariate regression on the covariates. The regression is estimated using the EM algorithm, and requires the numerical calculation of a multivariate integral. An example using simulated cognitive developmental data is presented, which shows that the estimation of individual variation in the parameters of a probability model may have substantial theoretical importance, even when individual differences are not the focus of the investigator's concerns.Research contributing to this article was supported by B.R.S. Subgrant 5-35345 from the University of Virginia. I thank the DADA Group, Bill Fabricius, Don Hartmann, William Griffin, Jack McArdle, Ivo Molenaar, Ronald Schoenberg, Simon Tavaré, and several anonymous reviewers for their discussion of these points.     

The internal structure of English transitive sentences

A major question in psychology is whether the same mechanisms are required for language learning and processing as for other cognitive tasks. A substantial body of literature has shown that natural categories are organized around a prototype, with other category members resembling the prototype to a greater or lesser amount based on the degree of shared properties. In order to investigate whether the prototype notion could be extended to linguistic phenomena, adult students (N=148) rated 512 sentences on a 7-point scale as to their goodness of fit to the categoryEnglish transitive sentence. Sentences differed in the animacy fo their actors and patients, the noun pairs used as actor/patient exemplars, and the hypothesized prototypicality of their verbs. Each of the identified factors showed the spread in ranking across different exemplars that is typical of other natural categories, but the factors interacted with each in complex ways to determine the overall ranking of the sentence. Not all sentences were equally representative of the categoryEnglish transitive sentence. In general, sentences with animate actors, high-prototypicality verbs, and animate patients were the most prototypical, followed closely by sentences with animate actors high-prototypicality verbs, and inanimate patients. Results were consistent with the suggestion that language and other types of cognitive tasks require the same basic processes and structures.     

ConPar: a method for identifying groups of concordant subject proximity matrices for subsequent multidimensional scaling analyses

A common representation of data within the context of multidimensional scaling (MDS) is a collection of symmetric proximity (similarity or dissimilarity) matrices for each of M subjects. There are a number of possible alternatives for analyzing these data, which include: (a) conducting an MDS analysis on a single matrix obtained by pooling (averaging) the M subject matrices, (b) fitting a separate MDS structure for each of the M matrices, or (c) employing an individual differences MDS model. We discuss each of these approaches, and subsequently propose a straightforward new method (CONcordance PARtitioning—ConPar), which can be used to identify groups of individual-subject matrices with concordant proximity structures. This method collapses the three-way data into a subject×subject dissimilarity matrix, which is subsequently clustered using a branch-and-bound algorithm that minimizes partition diameter. Extensive Monte Carlo testing revealed that, when compared to K-means clustering of the proximity data, ConPar generally provided better recovery of the true subject cluster memberships. A demonstration using empirical three-way data is also provided to illustrate the efficacy of the proposed method.     

伪科学活动中的人员构成探析

伪科学的英文表达是Pseudo-Science,Pseudo是有假的、伪的、冒充的含义,由此可见,伪科学就是:表面上打着科学旗号,实质上却违背科学本质的虚伪骗人学说。伪科学活动是一种世界性的现象,近年来在中国大地呈蔓延泛滥之势,给社会稳定和人民生活造成了极大的危害。整个伪科学活动主要包括三个环节:生产环节、传播环节和接受环节。一、伪科学的炮制者(1)伪科学家和科技工作者。一种是某些科学家为了得出“突破性”的发现,而对观察到的一些现象作出违背科学基本现象的解释,提出“新”的理论,以便一鸣惊人,这种现象称为病态科学现象。病态科学在…     

The proximity structure of achromatic surface colors and the impossibility of asymmetric lightness matching

In asymmetric lightness matching tasks, observers sometimes report that they cannot achieve satisfactory matches between achromatic surfaces under different neutral illuminants. The surfaces appear different, yet no further adjustment of either surface improves the match. There are evident difficulties in interpreting data from a task that the observer cannot always do, and these difficulties likely affect the interpretation of a large number of previous studies. We investigated, as an alternative to asymmetric matching, the direct use of proximity judgments in the study of surface lightness perception. We asked observers to rate the perceived dissimilarity of pairs of achromatic surfaces that were placed in identical scenes and viewed under different neutral illuminants. We develop a parametric model that accurately predicts perceived dissimilarity in terms of physical light intensities and surface albedos. The parameters of this model are readily interpretable. In particular, the ratio of the influence of changes in illuminant intensity and changes in surface albedo is a measure of the extent to which the observer discounts the illuminant. Asymmetric lightness matching can be interpreted as an unachievable limiting case of proximity judgment.     

Solving combinatorial problems: The 15-puzzle

We present a series of experiments in which human subjects were tested with a well-known combinatorial problem called the 15-puzzle and in different-sized variants of this puzzle. Subjects can solve these puzzles reliably by systematically building a solution path, without performing much search and without using distances among the states of the problem. The computational complexity of the underlying mental mechanisms is very low. We formulated a computational model of the underlying cognitive processes on the basis of our results. This model applied a pyramid algorithm to individual stages of each problem. The model's performance proved to be quite similar to the subjects' performance.     

Family resemblances: Studies in the internal structure of categories

Six experiments explored the hypothesis that the members of categories which are considered most prototypical are those with most attributes in common with other members of the category and least attributes in common with other categories. In probabilistic terms, the hypothesis is that prototypicality is a function of the total cue validity of the attributes of items. In Experiments 1 and 3, subjects listed attributes for members of semantic categories which had been previously rated for degree of prototypicality. High positive correlations were obtained between those ratings and the extent of distribution of an item's attributes among the other items of the category. In Experiments 2 and 4, subjects listed superordinates of category members and listed attributes of members of contrasting categories. Negative correlations were obtained between prototypicality and superordinates other than the category in question and between prototypicality and an item's possession of attributes possessed by members of contrasting categories. Experiments 5 and 6 used artificial categories and showed that family resemblance within categories and lack of overlap of elements with contrasting categories were correlated with ease of learning, reaction time in identifying an item after learning, and rating of prototypicality of an item. It is argued that family resemblance offers an alternative to criterial features in defining categories.     

The weight of obesity in evaluating others: a mere proximity effect

Previous research demonstrates that we tend to derogate individuals who are perceived to be in a social relationship with stigmatized persons. Two experiments examined whether this phenomenon also occurs for individuals seen in the presence of an obese person and whether a social relationship is necessary for stigmatization to spread. The results from both experiments revealed that a male job applicant was rated more negatively when seen with an overweight compared to a normal weight female and that just being in the mere proximity of an overweight woman was enough to trigger stigmatization toward the male applicant. Experiment 2 examined possible moderating effects of the proximity finding. Applicants seated next to heavy (vs. average weight) individuals were denigrated consistently regardless of the perceived depth of the relationship, the participant's anti-fat attitudes or gender, and whether or not positive information was presented concerning the woman. The profound nature of the obesity stigma and implications for impression formation processes are discussed.     

The proximity heuristic in judgments of accident probabilities

In daily life, probabilities are often assessed informally through the perceived distance to a target event. Accident probabilities are believed to be high when a disastrous outcome appears to be close. This proximity heuristic can lead to exaggerated p(death) estimates in risky situations (Experiment 2), and sometimes higher probabilities for death after near‐accidents than after actual accidents (Experiment 3 and 4). Near‐accidents are also believed to be equally good, or better, predictors of future disasters than actual accidents, despite being less serious and more frequent (Experiment 5). The proximity heuristic influences the way people talk about their own and other people's chances (Experiment 1), and how they prepare to avoid (or, if necessary, to produce) a disastrous outcome (Experiment 6).     

The fractal property of internal structure of facial affect recognition: A complex system approach

Based on a circumplex model of facial affect, four inner affective circumplexes, assumed to have 100%, 75%, 50%, and 25% emotional intensities, were investigated in terms of fractal, which is a concept of complex systems. Results revealed that the perimeters of the circumplex excluding the 25% condition possessed fractal property characterised by features specific to fractals. Results also showed that fractal dimension in the 50% condition (1.58 dimension) was significantly higher than that in the 100% (1.45 dimension) and 75% (1.45 dimension) conditions, indicating that the cognitive structure of facial affect in the 50% condition was more complex than that in the 100% and 75% conditions.     

A cross-cultural examination of proximity and hierarchy as dimensions of family structure

Meaningful cross-cultural application of family therapy theories requires that basic assumptions about normal family functioning be made explicit, and contextual factors be incorporated into the theories. Guided by this understanding, this article examines the family structure dimensions of proximity and generational hierarchy theoretically and empirically. These dimensions and their superordinate construct, boundary permeability, are analyzed in terms of their underlying assumptions. The cross-cultural validity of the dimensions is assessed using videotaped interactions, projective drawings, and interviews with a sample of 24 Turkish families. Results indicate that proximity is a valid dimension, moderated by the demographic variables of socioeconomic status (SES), mother's working status, family size, and clinical status. Hierarchy is not a valid dimension because the cultural norm of strong hierarchy suppresses variation. The implications for the cross-cultural transfer of family therapy theories are discussed.     

The wisdom of the crowd in combinatorial problems

The "wisdom of the crowd" phenomenon refers to the finding that the aggregate of a set of proposed solutions from a group of individuals performs better than the majority of individual solutions. Most often, wisdom of the crowd effects have been investigated for problems that require single numerical estimates. We investigate whether the effect can also be observed for problems where the answer requires the coordination of multiple pieces of information. We focus on combinatorial problems such as the planar Euclidean traveling salesperson problem, minimum spanning tree problem, and a spanning tree memory task. We develop aggregation methods that combine common solution fragments into a global solution and demonstrate that these aggregate solutions outperform the majority of individual solutions. These case studies suggest that the wisdom of the crowd phenomenon might be broadly applicable to problem-solving and decision-making situations that go beyond the estimation of single numbers.