Measuring Moral Progress

The study provides an in-depth analysis of two young adult subjects from a longitudinal study who underwent successive and significant developmental changes. Their developmental patterns, however, are only revealed by a new conception of moral stages, which is both more comprehensive and more detailed than Kohlberg’s original approach. In particular, the suggested alternative taxonomy neatly accommodates what appears as developmental anomalies in the Kohlbergian frame of reference. What is more, apart from merely matching with the observed data, the new theory also explains why the subjects developed the way they did, since it reveals the inherent cognitive conflicts at each stage and how these are resolved at the following one. Although the theory stands against the Kohlberg theory as it is, it may be understood as an extension and further development of the latter, in the sense that Kohlbergian stages are differentiated, supplemented, and theoretically substantiated within the new framework.

A class of multidimensional IRT models for testing unidimensionality and clustering items

We illustrate a class of multidimensional item response theory models in which the items are allowed to have different discriminating power and the latent traits are represented through a vector having a discrete distribution. We also show how the hypothesis of unidimensionality may be tested against a specific bidimensional alternative by using a likelihood ratio statistic between two nested models in this class. For this aim, we also derive an asymptotically equivalent Wald test statistic which is faster to compute. Moreover, we propose a hierarchical clustering algorithm which can be used, when the dimensionality of the latent structure is completely unknown, for dividing items into groups referred to different latent traits. The approach is illustrated through a simulation study and an application to a dataset collected within the National Assessment of Educational Progress, 1996. The author would like to thank the Editor, an Associate Editor and three anonymous referees for stimulating comments. I also thank L. Scaccia, F. Pennoni and M. Lupparelli for having done part of the simulations.     

A Statistical Interpretive Method for Neuropsychological Test Data

The accurate interpretation of large numbers of neuropsychological tests within a flexible battery approach is a difficult and sometimes controversial process. We present a statistically based method of interpretation (Rohling's Interpretive Method or RIM) and evaluation of neuropsychological data that allows for varying numbers of tests along a varying number of cognitive domains, yet remains psychometrically based. This method requires informed clinical judgment in that the level of confidence for tests, cognitive domains, and global indices are used as the backdrop for interpretive decisions. Specific procedures for use are presented in a systematic, detailed fashion to allow the interested reader to replicate the method. Two case examples are presented: a straightforward case of cerebrovascular insult and a more complicated case of mixed etiology. Examples include a variety of different neuropsychological tests commonly used in a flexible battery approach. A discussion of the practicality, ease of use, and potential limitations of this method are further presented.     

A method for analyzing changes in response efficiency.

Although experimental effects typically are evaluated by summarizing levels of responding across time (e.g., calculating the mean levels of problem behavior during 10‐min sessions), these data summaries may obscure important mechanisms that may be responsible for changes in responding. A case study is reported to illustrate alternative methods of data analysis when decreasing trends in responding may be due to increases in response efficiency.     

关系研究的新取向：社会网络分析

社会网络分析（Social Network Analysis, SNA）是用社会实体之间的关系来描述、解释和预测社会现象的一种研究取向。SNA提供了深入探究社会环境特征及其对个体心理发展影响的一种方法。本文基于SNA的发展历程,依次介绍了中心性分析、小团体分析、位置分析、QAP以及统计模型法。SNA在社会学研究中得到了较多应用,近年来在心理学研究中开始受到重视。     

Normative values on the marks and mathews fear questionnaire: A comparison as a function of age and sex

While the Marks and Mathews Fear Questionnaire (1979) has gained widespread use, little information on its psychometric characteristics has been reported. Thus, one purpose of this investigation was to provide normative information on this device. A second purpose was to examine differences in reported fears as a function of age and sex. Fear Questionnaires were administered to a large sample of high-school students, college students, and adults. Means and standard deviations on the Fear Questionnaire are reported for the various groups. Significant differences were found between groups, with college and high-school women reporting more fears than corresponding men, college and high-school women reporting more fears than adult women, and college men showing a trend toward more fears than other men.Portions of this paper were presented at the Annual Meeting of the Association for the Advancement of Behavior Therapy, November 1985, Houston, Texas.     

Polytomous IRT models and monotone likelihood ratio of the total score

In a broad class of item response theory (IRT) models for dichotomous items the unweighted total score has monotone likelihood ratio (MLR) in the latent trait. In this study, it is shown that for polytomous items MLR holds for the partial credit model and a trivial generalization of this model. MLR does not necessarily hold if the slopes of the item step response functions vary over items, item steps, or both. MLR holds neither for Samejima's graded response model, nor for nonparametric versions of these three polytomous models. These results are surprising in the context of Grayson's and Huynh's results on MLR for nonparametric dichotomous IRT models, and suggest that establishing stochastic ordering properties for nonparametric polytomous IRT models will be much harder.Hemker's research was supported by the Netherlands Research Council, Grant 575-67-034. Junker's research was supported in part by the National Institutes of Health, Grant CA54852, and by the National Science Foundation, Grant DMS-94.04438.     

The relationship between Fisher's exact test and Pearson's chi-square test: A bayesian perspective

It is demonstrated in this paper that two major tests for 2 × 2 talbes are highly related from a Bayesian perspective. Although it is well-known that Fisher's exact and Pearson's chi-square tests are asymptotically equivalent, the present analysis shows that a formal similarity also exists in small samples. The key assumption that leads to the resemblance is the presence of a continuous parameter measuring association. In particular, it is shown that Pearson's probability can be obtained by integrating a two-moment approximation to the posterior distribution of the log-odds ratio. Furthermore, Pearson's chi-square test gave an excellent approximation to the actual Bayes probability in all 2×2 tables examined, except for those with extremely disproportionate marginal frequencies.     

Models for measurement,precision, and the nondichotomization of graded responses

It is common in educational, psychological, and social measurement in general, to collect data in the form of graded responses and then to combine adjacent categories. It has been argued that because the division of the continuum into categories is arbitrary, any model used for analyzing graded responses should accommodate such action. Specifically, Jansen and Roskam (1986) enunciate ajoining assumption which specifies that if two categoriesj andk are combined to form categoryh, then the probability of a response inh should equal the sum of the probabilities of responses inj andk. As a result, they question the use of the Rasch model for graded responses which explicitly prohibits the combining of categories after the data are collected except in more or less degenerate cases. However, the Rasch model is derived from requirements of invariance of comparisons of entities with respect to different instruments, which might include different partitions of the continuum, and is consistent with fundamental measurement. Therefore, there is a strong case that the mathematical implication of the Rasch model should be studied further in order to understand how and why it conflicts with the joining assumption. This paper pursues the mathematics of the Rasch model and establishes, through a special case when the sizes of the categories are equal and when the model is expressed in the multiplicative metric, that its probability distribution reflects the precision with which the data are collected, and that if a pair of categories is collapsed after the data are collected, it no longer reflects the original precision. As a consequence, and not because of a qualitative change in the variable, the joining assumption is destroyed when categories are combined. Implications of the choice between a model which satisfies the joining assumption or one which reflects on the precision of the data collection considered are discussed.