On the importance of distinguishing between within- and between-subject effects in intransitive intertemporal choice

Most probabilistic paired comparison models treat inconsistent choices as caused by independent and random errors in the pairwise judgments. In this paper, we argue that this assumption is too restrictive for the analysis of paired comparison data obtained from multiple judges when transitivity violations are systematic. We present a new framework that contains the random error assumption as a special case but also allows for systematic changes in an option's utility assessments over the pairwise comparisons. Accounting for both between- and within-judge sources of variability, we demonstrate in an application on intertemporal choice that the proposed framework can capture systematic transitivity violations as well as individual taste differences.     

Assessing vocational interests in the Basque Country using paired comparison design

This article proposes the Thurstonian paired comparison model to assess vocational preferences and uses this approach to evaluate the Realistic, Investigative, Artistic, Social, Enterprise, and Conventional (RIASEC) model in the Basque Country (Spain). First, one unrestricted model is estimated in the Structural Equation Modelling framework using one paired comparison design. Secondly, the RIASEC circumplex structure is evaluated upon the estimated latent preferences correlation matrix. The results show good fit between the Thurstonian model and the data, but do not confirm the RIASEC structure in the Basque population.     

Classroom climate and students' goal preferences: a cross-cultural comparison

Goal preferences indicate intentions to achieve or avoid particular states. We examined whether Curacaoan and Dutch students differ in goal preferences related to school and whether goal preferences are associated with students' evaluation of the classroom climate. Measurement invariance of the instruments was also tested between samples. Participants attended vocational high schools in Curacao ( N = 276) or in the Netherlands ( N = 283). Both the classroom climate and goal preferences differed between the samples. In the Netherlands the preference for individuality, belongingness, and recognition was stronger, whereas in Curacao mastery, satisfaction, self-determination, and material gain were more frequently endorsed. The two variables were modestly correlated. Schools do have a globalizing effect on students' school experiences and hardly adapt to goal preferences. The latter seem to be affected by non-school related cultural factors.     

Examining business students' career preferences: A perceptual space approach

A methodology for examining career preferences is proposed. The method uses perceptual mapping techniques and external preference analysis to assess the attributes individuals believe are important. The results of a study undertaken to test the methodology are reported and it appears that such results can be useful in analyzing reasons for career preferences.     

Modelling pedestrian crossing behaviour in urban roads: A latent variable approach

As pedestrians are the most exposed and vulnerable road users to traffic accidents, urban planners frequently propose alternatives to improve their safety. However, some solutions, such as pedestrian bridges and crosswalks at signalized intersections, usually imply longer walking distances compared to the direct crossing alternative which, in its turn, involves a higher risk.In this article, a hybrid framework is proposed to analyse the pedestrians’ choice on how to cross an urban road where three crossing options are available: crossing directly, crossing by using a pedestrian bridge or using a crosswalk at a signalized intersection. The decision process is modelled as a discrete choice model incorporating latent variables to consider perceptions and psychological factors, using stated preference data coming from a survey applied in Bogotá, Colombia.Results show that the latent variables security/safety and attractiveness of each crossing alternative are relevant to understand the pedestrian crossing behaviour. These latent variables are strongly determined by socioeconomic characteristics of the individual (age, gender, level of study) and conditioned by the circumstances of the trip (main mode of transport, walking or not with children). It was found that a longer walking distance to a pedestrian bridge or a signalized crosswalk increases the probability of direct crossing, having a more relevant effect in the case of the pedestrian bridge.     

Split identity: intransitive judgments of the identity of objects

Identity is a transitive relation, according to all standard accounts. Necessarily, if x = y and y = z, then x = z. However, people sometimes say that two objects, x and z, are the same as a third, y, even when x and z have different properties (thus, x = y and y = z, but x ≠ z). In the present experiments, participants read stories about an iceberg that breaks into two icebergs, one to the east and the other to the west. Many participants (32–54%, in baseline conditions across experiments) decided that both successors were the original iceberg, despite the different spatial locations of the successors. Experiment 1 shows that this tendency is not due to participants failing to understand both to mean both are simultaneously the original. Similarly, Experiment 2 demonstrates that the tendency is not solely due to their interpreting the question to be about properties of the icebergs rather than about the icebergs themselves. Experiments 3 and 4 suggest, instead, that participants may understand Which is the original? to mean Which, in its own right, is entitled to be the original? Emphasizing entitlement increases the number of seemingly intransitive responses, whereas emphasizing the formal properties of identity decreases them.     

Contrast effects in typicality judgements: A hierarchical Bayesian approach

We examine the influence of contrast categories on the internal graded membership structure of everyday concepts using computational models proposed in the artificial category learning tradition. In particular, the generalized context model (Nosofsky, 1986), which assumes that only members of a given category contribute to the typicality of a category member, is contrasted to the similarity–dissimilarity generalized context model (SD-GCM; Stewart & Brown, 2005), which assumes that members of other categories are also influential in determining typicality. The models are compared in a hierarchical Bayesian framework in their account of the typicality gradient of five animal categories and six artefact categories. For each target category, we consider all possible relevant contrast categories. Three separate issue are examined: (a) whether contrast effects can be found, (b) which categories are responsible for these effects, and (c) whether more than one category influences the typicality. Results indicate that the internal category structure is codetermined by dissimilarity towards potential contrast categories. In most cases, only a single contrast category contributed to the typicality. The present findings suggest that contrast effects might be more widespread than has previously been assumed. Further, they stress the importance of characteristics particular of everyday concepts, which require careful consideration when applying computational models of representation of the artificial category learning tradition to everyday concepts.     

Motivation modulates the effect of approach on implicit preferences

With three studies, we investigated whether motivational states can modulate the formation of implicit preferences. In Study 1, participants played a video game in which they repeatedly approached one of two similar beverages, while disregarding the other. A subsequent implicit preference for the target beverage emerged, which increased with participants’ thirst. In Study 2, participants approached one brand of potato chips while avoiding the other: Conceptually replicating the moderation observed in Study 1, the implicit preference for the approached brand increased with the number of hours from last food intake. In Study 3, we experimentally manipulated hunger, and the moderation effect emerged again, with hungry participants displaying a higher implicit preference for the approached brand, as compared to satiated participants. In the three studies, the moderation effect was not paralleled in explicit preferences although the latter were affected by the preference inducing manipulation. Theoretical implications and open questions are discussed.     

Comparing the perceived causes of the second Iraq war: a network analysis approach

The objective of this research was to examine the representation by British students of 11 perceived causes of the invasion of Iraq. We used network analysis to develop a network of the pattern of causes that are involved. Overall most participants identified a nexus of causes that reciprocally linked religious prejudice, racism and the history of conflict in the Middle East. They identified a reciprocal link between religious prejudice and September 11th, indicating that it was a cause and effect of religious prejudice. They also supported a link between the personalities of Bush and Saddam and economic gain, and acknowledged the effect of the first Gulf war on Saddam. We also found that Muslim participants were significantly less in favour of the invasion than Christian participants, and produced different networks of the links between causes. The study demonstrates that network analysis can be used to compare and contrast representations of a political event, and thus extends its use in the study of social representations. Aggr. Behav. 32:321–329, 2006. © 2006 Wiley‐Liss, Inc.     

Modelling partially cross‐classified multilevel data

This article proposes an approach to modelling partially cross‐classified multilevel data where some of the level‐1 observations are nested in one random factor and some are cross‐classified by two random factors. Comparisons between a proposed approach to two other commonly used approaches which treat the partially cross‐classified data as either fully nested or fully cross‐classified are completed with a simulation study. Results show that the proposed approach demonstrates desirable performance in terms of parameter estimates and statistical inferences. Both the fully nested model and the fully cross‐classified model suffer from biased estimates of some variance components and statistical inferences of some fixed effects. Results also indicate that the proposed model is robust against cluster size imbalance.     

A note on dual scaling of successive categories data

Three methods for dual scaling of successive categories data are formulated. They are mathematically equivalent, and provide an appropriate technique to determine stimulus values and category boundaries on a joint scale, a problem that Nishisato's method (1980a) failed to handle. This study was supported by the Natural Sciences and Engineering Research Council of Canada (Grant No. A7942) to S. Nishisato. Comments on the earlier draft from anonymous reviewers were most helpful and much appreciated.     

A maximum likelihood approach to test validation with missing and censored dependent variables

A maximum likelihood approach is described for estimating the validity of a test (x) as a predictor of a criterion variable (y) when there are both missing and censoredy scores present in the data set. The missing data are due to selection on a latent variable (y _s ) which may be conditionally related toy givenx. Thus, the missing data may not be missing random. The censoring process in due to the presence of a floor or ceiling effect. The maximum likelihood estimates are constructed using the EM algorithm. The entire analysis is demonstrated in terms of hypothetical data sets.     

社会比较研究的现状与发展趋势

社会比较是人类普遍存在的一种社会现象,在西方关于社会比较的研究已经成为心理学界的一个重要课题。该文从社会比较的概念、类型、动机和策略等几个方面,回顾了国外近50年来研究者关于社会比较的研究脉络;最后,在回顾近几年研究的基础上对社会比较的未来研究趋势进行了展望。     

A multimethod approach to examining usability of Web privacy polices and user agents for specifying privacy preferences

Because all research methods have strengths and weaknesses, a multimethod approach often provides the best way to understand human behavior in applied settings. We describe how a multimethod approach was employed in a series of studies designed to examine usability issues associated with two aspects of online privacy: comprehension of privacy policies and configuration of privacy preferences for an online user agent. Archival research, user surveys, data mining, quantitative observations, and controlled experiments each yielded unique findings that, together, contributed to increased understanding of online-privacy issues for users. These findings were used to evaluate the accessibility of Web privacy policies to computer-literate users, determine whether people can configure user agents to achieve specific privacy goals, and discover ways in which the usability of those agents can be improved.     

A general approach to categorical data analysis with missing data,using generalized linear models with composite links

A general approach for analyzing categorical data when there are missing data is described and illustrated. The method is based on generalized linear models with composite links. The approach can be used (among other applications) to fill in contingency tables with supplementary margins, fit loglinear models when data are missing, fit latent class models (without or with missing data on observed variables), fit models with fused cells (including many models from genetics), and to fill in tables or fit models to data when variables are more finely categorized for some cases than others. Both Newton-like and EM methods are easy to implement for parameter estimation.The author thanks the editor, the reviewers, Laurie Hopp Rindskopf, and Clifford Clogg for comments and suggestions that substantially improved the paper.     

A bayesian approach to confirmatory factor analysis

Confirmatory factor analysis is considered from a Bayesian viewpoint, in which prior information on parameter is incorporated in the analysis. An iterative algorithm is developed to obtain the Bayes estimates. A numerical example based on longitudinal data is presented. A simulation study is designed to compare the Bayesian approach with the maximum likelihood method.Computer facilities were provided by the Computer Services Center, The Chinese University of Hong Kong.