Additive conjoint isotonic probabilistic models (ADISOP)

The ISOP-model or model of twodimensional or bi-isotonicity (Scheiblechner, 1995) postulates that the probabilities of ordered response categories increase isotonically in the order of subject ability and item easiness. Adding a conventional cancellation axiom for the factors of subjects and items gives the ADISOP model where the c.d.f.s of response categories are functions of an additive item and subject parameter and an ordinal category parameter. Extending cancellation to the interactions of subjects and categories as well as of items and categories (independence axiom of the category factor from the subject and item factor) gives the CADISOP model (completely additive model) in which the parallel c.d.f.s are functions of the sum of subject, item and category parameters. The CADISOP model is very close to the unidimensional version of the polytomous Rasch model with the logistic item/category characteristic(s) replaced by nonparametric axioms and statistics. The axioms, representation theorems and algorithms for model fitting of the additive models are presented.     

The Application of Latent Curve Analysis to Testing Developmental Theories in Intervention Research

The effectiveness of a prevention or intervention program has traditionally been assessed using time-specific comparisons of mean levels between the treatment and the control groups. However, many times the behavior targeted by the intervention is naturally developing over time, and the goal of the treatment is to alter this natural or normative developmental trajectory. Examining time-specific mean levels can be both limiting and potentially misleading when the behavior of interest is developing systematically over time. It is argued here that there are both theoretical and statistical advantages associated with recasting intervention treatment effects in terms of normative and altered developmental trajectories. The recently developed technique of latent curve (LC) analysis is reviewed and extended to a true experimental design setting in which subjects are randomly assigned to a treatment intervention or a control condition. LC models are applied to both artificially generated and real intervention data sets to evaluate the efficacy of an intervention program. Not only do the LC models provide a more comprehensive understanding of the treatment and control group developmental processes compared to more traditional fixed-effects models, but LC models have greater statistical power to detect a given treatment effect. Finally, the LC models are modified to allow for the computation of specific power estimates under a variety of conditions and assumptions that can provide much needed information for the planning and design of more powerful but cost-efficient intervention programs for the future.     

Normativity,Guardianship, and the Elderly

The concept of guardianship, its associated principles, distinctions, and articulation of the legal needs of the elderly are introduced via a review of well-canvassed criticisms of Canadian guardianship legislation. Claims that the reformed legislation of Alberta, Quebec, and British Columbia represent models of adequate adult guardianship compared with traditional (archaic lunacy) law are examined. This paper argues that these renovated models exhibit a dubious normative advance over traditional legislation. Specifically, the normative presuppositions of the reformed legislation, such as, restriction to an autonomy-paternalism framework, and the norms of the liberal individual and state, obscure important issues in at least two key areas which challenge the models' assumptions; namely, assessment and legal competence and assessment and need. The development of guardianship laws and of social arrangements that are more responsive to the life experiences of the elderly requires critical re-articulation of the nature of individuals and their communities.     

结构对称性汉语成语的认知研究

运用命名作业,从识别和再认两个方面探讨了结构对称性汉语成语的认知特点,结果发现：（１）成语识别有显著的结构对称效应和熟悉度效应;结构对称性成语的识别明显快于非对称性成语,高熟悉度成语的识别明显快于低熟悉度的成语。（２）成语再认的反应时有显著的结构对称效应,熟悉度效应不显著;而反应错误率则有显著的熟悉度效应,结构对称效应不显著。上述结果都不存在结构对称性和熟悉度之间的显著的交互作用。现有的西方拼音文字认知模型不能恰当地解释汉语成语的认知特点。     

SOCIAL INTERACTIONS IN THREE SUPPORTED EMPLOYMENT OPTIONS: A COMPARATIVE ANALYSIS

Controversy exists over the benefits that workers with severe disabilities accrue under different supported employment options. This study focused upon one benefit of supported employment: social integration. Direct observation procedures were used to assess the social interactions of 37 adults with severe disabilities in 18 employment programs representing three different supported employment contexts (individual, enclave, and work crew). Results indicated that workers employed in individual and enclave programs had significantly more contact with nondisabled persons than did members of work crews. No differences were detected in the social contact rate between disabled and nondisabled workers in individual versus enclave sites. Furthermore, few differences in type of interactions across the three different work options were revealed. Results suggest that both individual and enclave models are capable of facilitating social integration. However, characteristics of specific job sites, more so than the employment model per se, may determine whether a particular employment setting is conducive to social integration.     

Comparing the predictive powers of alternative multiple regression models

Mean squared error of prediction is used as the criterion for determining which of two multiple regression models (not necessarily nested) is more predictive. We show that an unrestricted (or true) model witht parameters should be chosen over a restricted (or misspecified) model withm parameters if (P _t ² ?P _m ² )>(1?P _t ² )(t?m)/n, whereP _t ² andP _m ² are the population coefficients of determination of the unrestricted and restricted models, respectively, andn is the sample size. The left-hand side of the above inequality represents the squared bias in prediction by using the restricted model, and the right-hand side gives the reduction in variance of prediction error by using the restricted model. Thus, model choice amounts to the classical statistical tradeoff of bias against variance. In practical applications, we recommend thatP ² be estimated by adjustedR ² . Our recommendation is equivalent to performing theF-test for model comparison, and using a critical value of 2?(m/n); that is, ifF>2?(m/n), the unrestricted model is recommended; otherwise, the restricted model is recommended.     

Perception: The interface between cognition and the external world

In contrast to researchers who emphasize the distinction between perception and cognition it is claimed that the perceptual system is closely intertwined with cognition and with our comprehension of the external world. This claim is supported by evidence for two characteristic features of human information processing. One of these features is the use of mental models. If mental models are assumed to be anchored in the perceptual system it will not be necessary to assume a "little man in the head" who reads off the model. Moreover, perceptually based mental models will provide a referential semantics by anchoring mentally represented concepts in the external world. The other feature is the use of perceptually based perspectives in cognition, such as actor or observer perspectives in social cognition. It is concluded that human beings consistently interact within the real world--also when they are just thinking--and that this becomes possible via perceptual processes.     

Principal component analysis with external information on both subjects and variables

A method for structural analysis of multivariate data is proposed that combines features of regression analysis and principal component analysis. In this method, the original data are first decomposed into several components according to external information. The components are then subjected to principal component analysis to explore structures within the components. It is shown that this requires the generalized singular value decomposition of a matrix with certain metric matrices. The numerical method based on the QR decomposition is described, which simplifies the computation considerably. The proposed method includes a number of interesting special cases, whose relations to existing methods are discussed. Examples are given to demonstrate practical uses of the method.The work reported in this paper was supported by grant A6394 from the Natural Sciences and Engineering Research Council of Canada to the first author. Thanks are due to Jim Ramsay, Haruo Yanai, Henk Kiers, and Shizuhiko Nishisato for their insightful comments on earlier versions of this paper. Jim Ramsay, in particular, suggested the use of the QR decomposition, which simplified the presentation of the paper considerably.     

A generalized rasch model for manifest predictors

A logistic regression model is suggested for estimating the relation between a set of manifest predictors and a latent trait assumed to be measured by a set ofk dichotomous items. Usually the estimated subject parameters of latent trait models are biased, especially for short tests. Therefore, the relation between a latent trait and a set of predictors should not be estimated with a regression model in which the estimated subject parameters are used as a dependent variable. Direct estimation of the relation between the latent trait and one or more independent variables is suggested instead. Estimation methods and test statistics for the Rasch model are discussed and the model is illustrated with simulated and empirical data.     

A simple multivariate probabilistic model for preferential and triadic choices

Multidimensional probabilistic models of behavior following similarity and choice judgements have proven to be useful in representing multidimensional percepts in Euclidean and non-Euclidean spaces. With few exceptions, these models are generally computationally intense because they often require numerical work with multiple integrals. This paper focuses attention on a particularly general triad and preferential choice model previously requiring the numerical evaluation of a 2n-fold integral, wheren is the number of elements in the vectors representing the psychological magnitudes. Transforming this model to an indefinite quadratic form leads to a single integral. The significance of this form to multidimensional scaling and computational efficiency is discussed.The authors would like to thank Jean-Claude Falmagne and Norman Johnson for suggestions and advice concerning quadratic forms.