Comparing Moral Education Models at a Military Academy in Taiwan

This study compared the effects of three education models, namely, the bag-of-virtues (BV), values clarification (VC), and virtue ethics (VE) models, through qualitative and quantitative approaches. In the quantitative study (Study 1), a between-subjects design was adopted in sampling 120 freshman cadets from a Taiwanese military academy. For the qualitative study (Study 2), focus group interviews were conducted with 10 freshman cadets. The results show that the VC model was the most effective among the three moral education models, followed by the VE and BV models.     

The living legacy of the Harvard Pigeon Lab: quantitative analysis in the wide world

From the Harvard Pigeon Lab of the 1960s arose a behavior-analytic approach that was quantitative and rigorous, rooted in Herrnstein's matching law. Researchers modified the matching law to describe choice behavior in a variety of different settings and examined its relations with other quantitative models. Beginning in the early 1970s, researchers began using the Harvard Pigeon Lab's quantitative framework to study in the laboratory specific aspects of the world outside the laboratory. Much of this work concerned investigations of self-control-choice of a larger, more delayed reinforcer over a smaller, less delayed reinforcer. Experiments using a quantitative framework derived from the matching law have also been conducted outside the laboratory; however, these have been far less frequent. Current and future researchers will benefit the field by devising new, creative ways to investigate the matching law and related quantitative models outside the laboratory. Such research can help to demonstrate the validity of these models as basic principles of behavior, can enhance public opinion of and rewards for such research, and can stimulate further development of the Harvard Pigeon Lab's quantitative approach by using that approach with new variables.     

多项式加工树模型次序约束的量化分析及其应用

多项式加工树（MPT）模型是一种认知测量模型,能够对潜在认知过程进行测量和检验。已有研究探讨了二链MPT模型次序约束的重新参数化问题,本研究探讨了MPT模型次序约束的量化分析方法并从二链推广到多链,同时归纳出MPT模型参数向量内和参数向量间两参数次序约束量化分析的结论。数据分析结果表明该方法不仅在MPT模型框架下验证了潜在参数次序关系,而且给出了约束的量化指标,为潜在认知测量提供更有意义的解释。     

Indirect scaling methods for testing quantitative emotion theories

Two studies investigated the utility of indirect scaling methods, based on graded pair comparisons, for the testing of quantitative emotion theories. In Study 1, we measured the intensity of relief and disappointment caused by lottery outcomes, and in Study 2, the intensity of disgust evoked by pictures, using both direct intensity ratings and graded pair comparisons. The stimuli were systematically constructed to reflect variables expected to influence the intensity of the emotions according to theoretical models of relief/disappointment and disgust, respectively. Two probabilistic scaling methods were used to estimate scale values from the pair comparison judgements: Additive functional measurement (AFM) and maximum likelihood difference scaling (MLDS). The emotion models were fitted to the direct and indirect intensity measurements using nonlinear regression (Study 1) and analysis of variance (Study 2). Both studies found substantially improved fits of the emotion models for the indirectly determined emotion intensities, with their advantage being evident particularly at the level of individual participants. The results suggest that indirect scaling methods yield more precise measurements of emotion intensity than rating scales and thereby provide stronger tests of emotion theories in general and quantitative emotion theories in particular.     

Modeling Children's Understanding of Quantitative Relations in Texts: A Developmental Perspective

This article describes developmental models of word problem solving that are grounded in the notion of general developmental constraints of the mind. These models were constructed based on the assumption that differences in children's word problem-solving performance are due, at least in part, to developmental differences in their conceptual structures in the quantitative domain. Three levels of knowledge were identified and modeled. The simplest model represents quantitative relations as an ordered array of mental objects. The next level of the model represents numbers as objects of manipulations open two mental number lines that are coordinated in a tentative fashion. The most complex model represents numerical operations as objects of manipulations on two mental number lines that are well-coordinated with explicit, functional rules. These models were implemented as production systems. The accuracy of the predictions resulting from the simulations of the models was tested in an empirical study. Global tests of the models found a good fit of the data to the models. The results wee consistent with the theoretical analysis that the three levels of knowledge were internally coherent and qualitatively different from each other, and that the models could predict children's performance differences to a satisfactory degree.     

Analysis of multivariate mixed longitudinal data: A flexible latent process approach

Multivariate ordinal and quantitative longitudinal data measuring the same latent construct are frequently collected in psychology. We propose an approach to describe change over time of the latent process underlying multiple longitudinal outcomes of different types (binary, ordinal, quantitative). By relying on random‐effect models, this approach handles individually varying and outcome‐specific measurement times. A linear mixed model describes the latent process trajectory while equations of observation combine outcome‐specific threshold models for binary or ordinal outcomes and models based on flexible parameterized non‐linear families of transformations for Gaussian and non‐Gaussian quantitative outcomes. As models assuming continuous distributions may be also used with discrete outcomes, we propose likelihood and information criteria for discrete data to compare the goodness of fit of models assuming either a continuous or a discrete distribution for discrete data. Two analyses of the repeated measures of the Mini‐Mental State Examination, a 20‐item psychometric test, illustrate the method. First, we highlight the usefulness of parameterized non‐linear transformations by comparing different flexible families of transformation for modelling the test as a sum score. Then, change over time of the latent construct underlying directly the 20 items is described using two‐parameter longitudinal item response models that are specific cases of the approach.     

The mapping model: a cognitive theory of quantitative estimation

How do people make quantitative estimations, such as estimating a car's selling price? Traditionally, linear-regression-type models have been used to answer this question. These models assume that people weight and integrate all information available to estimate a criterion. The authors propose an alternative cognitive theory for quantitative estimation. The mapping model, inspired by the work of N. R. Brown and R. S. Siegler (1993) on metrics and mappings, offers a heuristic approach to decision making. The authors test this model against established alternative models of estimation, namely, linear regression, an exemplar model, and a simple estimation heuristic. With 4 experimental studies the authors compare the models under different environmental conditions. The mapping model proves to be a valid model to predict people's estimates.     

Diffusion models of the flanker task: Discrete versus gradual attentional selection

The present study tested diffusion models of processing in the flanker task, in which participants identify a target that is flanked by items that indicate the same (congruent) or opposite response (incongruent). Single- and dual-process flanker models were implemented in a diffusion-model framework and tested against data from experiments that manipulated response bias, speed/accuracy tradeoffs, attentional focus, and stimulus configuration. There was strong mimcry among the models, and each captured the main trends in the data for the standard conditions. However, when more complex conditions were used, a single-process spotlight model captured qualitative and quantitative patterns that the dual-process models could not. Since the single-process model provided the best balance of fit quality and parsimony, the results indicate that processing in the simple versions of the flanker task is better described by gradual rather than discrete narrowing of attention.     

Diffusion models of the flanker task: discrete versus gradual attentional selection

The present study tested diffusion models of processing in the flanker task, in which participants identify a target that is flanked by items that indicate the same (congruent) or opposite response (incongruent). Single- and dual-process flanker models were implemented in a diffusion-model framework and tested against data from experiments that manipulated response bias, speed/accuracy tradeoffs, attentional focus, and stimulus configuration. There was strong mimcry among the models, and each captured the main trends in the data for the standard conditions. However, when more complex conditions were used, a single-process spotlight model captured qualitative and quantitative patterns that the dual-process models could not. Since the single-process model provided the best balance of fit quality and parsimony, the results indicate that processing in the simple versions of the flanker task is better described by gradual rather than discrete narrowing of attention.     

Modelling age-related changes in information processing

Researchers in cognitive ageing seldom take advantage of explicit quantitative models of information processing to account for age differences in cognition. Where quantitative models have been used, these models typically remain silent about the details of information processing. The lack of explicit cognitive models has consequences for the interpretation of a number of empirical results. Using a specific class of models called random walk models, I review evidence showing that the empirical relations taken as support for global age-related changes are consistent with a number of possible age effects on information processing. In addition, I demonstrate that these models can be used to account for age differences within the context of individual experiments and such modelling has important implications for the interpretation of age differences in performance.     

Testing quantitative models of backward masking

We analyzed the relationship between U-shaped and monotonic-shaped masking functions, using both computer simulations of quantitative models and experimental data. Our analysis revealed that quantitative models of backward masking predict that U-shaped masking functions should appear for weak masks and monotonic masking functions should appear for strong masks. The models predict, moreover, that for a fixed target and experimental task, as the mask changes it is possible to go from U-shaped to monotonic-shaped masking functions. Significantly, the models predict that at each stimulus onset asynchrony between the target and the mask, the U-shaped function must have weaker masking than the monotonic-shaped function. Contrary to the predictions of the models, we show an experimental situation that generates masking functions that violate this prediction.     

Understanding the shear band interaction in metallic glass

Qualitative and quantitative models were proposed to understand the shear band (SB) interaction scenario found in the compressive tests on specimen with two symmetrical semi-circular notches. The so-called ‘work-hardening’ behavior could be ascribed as the stress interaction which was caused by stress fields around the SB tips. Besides, the SB bending was observed along propagation orientation. The quantitative analysis based on traditional shear deformation mechanism could reasonably account for how the SB was bent. It is anticipated that the present work could provide a pathway to understand the deep SB deformation mechanism of metallic glass.     

What Are We Doing When We Translate from Quantitative Models?

Although quantitative analysis (in which behavior principles are defined in terms of equations) has become common in basic behavior analysis, translational efforts often examine everyday events through the lens of narrative versions of laboratory-derived principles. This approach to translation, although useful, is incomplete because equations may convey concepts that are difficult to capture in words. To support this point, we provide a nontechnical introduction to selected aspects of quantitative analysis; consider some issues that translational investigators (and, potentially, practitioners) confront when attempting to translate from quantitative models; and discuss examples of relevant translational studies. We conclude that, where behavior-science translation is concerned, the quantitative features of quantitative models cannot be ignored without sacrificing conceptual precision, scientific and practical insights, and the capacity of the basic and applied wings of behavior analysis to communicate effectively.     

The importance of shared environmental influences in explaining the overlap between mother's parenting and sibling relationships: reply to Neale (1999)

This article addresses concerns raised by M. C. Neale (1999) in his commentary on the D. A. Bussell et al. (1999) Nonshared Environment in Adolescent Development (NEAD) study. These concerns fall into two categories: (a) model assumptions and sample design and (b) testing of alternative models. The validity of the assumptions of quantitative genetic models is a concern for all researchers in this area. Discussion of those assumptions in this reply is brief and focuses on those most relevant to the NEAD sample. The two alternative models proposed by Neale were designed to provide alternatives to the large shared environmental effect found in the original report of Bussell et al. Because these alternative models did not provide a better fit, the appropriateness of Bussell et al.'s basic model and the importance of shared environmental influences for explaining the association among family subsystems are supported.     

Genetic and environmental influences on behavior: capturing all the interplay

Basic quantitative genetic models of human behavioral variation have made clear that individual differences in behavior cannot be understood without acknowledging the importance of genetic influences. Yet these basic models estimate average, population-level genetic and environmental influences, obscuring differences that might exist within the population and masking systematic transactions between specific genetic and environmental influences. This article discusses a newer, more sophisticated and powerful quantitative genetic model that articulates these transactions. Results from this model highlight the ways in which the gene- environment interaction and correlation are intertwined. They can be used to integrate findings from quantitative and molecular genetic studies and to understand the roles of genetic influences and social forces in manifested behaviors, even when DNA sequence variation is not relevant.     

Adolescent depression and externalizing problems: testing two models of comorbidity in an inpatient sample

Differentiating between additive (quantitative) and interactive (qualitative) effects of comorbidity has important treatment implications. This study illustrates the heuristic superiority of a multifactorial approach over simple group comparisons in testing quantitative versus qualitative models of comorbidity. Analysis of variance was used to compare 266 adolescent inpatients identified as depressed, externalizing, both, or neither on self-report measures of personality, school problems, and substance abuse. The results support quantitative rather than qualitative models of comorbidity. Depressed status related most strongly to group differences in interpersonal and self-critical concerns. Externalizing status related most strongly to group differences in school problems and drug use. Main effects for the two statuses together explained especially elevated levels of reactance and alcohol abuse among the comorbid adolescents.