Overpredicting and Underprofiting in Pricing Decisions

This research examines sellers' price‐setting behavior and discovers a naturally occurring mismatch between sellers and buyers: Sellers who make a price decision often consider alternative prices and engage in the joint evaluation mode, whereas buyers who make a purchase decision see only the finally set price and are in the single evaluation mode. This mismatch in evaluation modes leads sellers to overpredict buyers' price sensitivity and underprice their products. However, these effects apply only to products unfamiliar to buyers and without salient reference prices and can be alleviated if sellers are encouraged to mimic single evaluation when making pricing decisions. These propositions are empirically tested and verified. Copyright © 2011 John Wiley & Sons, Ltd.     

Biased extensive measurement: The general case

We develop a theory of biased extensive measurement which allows us to prove the existence of a ratio-scale without transitivity of indifference and with a property of homothetic invariance weaker than independence. These representations, which cover the cases of interval orders and of semiorders, reveal a unique biasing function smaller or equal to 1 that distorts extensive measurement and explains departures from its standard axioms. We interpret this biasing function as characterizing the qualitative influence of the underlying measurement process and we show that it induces a proportional indifference threshold.     

Violence risk assessment in persons with mental illness

Mental health clinicians are often asked to determine an individual's risk of future violence. Dangerous assessments are required in a wide variety of situations that include involuntary commitments, emergency psychiatric evaluations, seclusion and restraint release decisions, inpatient care discharges, probation/parole decisions, death penalty evaluations, domestic violence interventions, fitness for duty evaluations, and after a threat is made. This article provides an overview regarding the assessment of dangerousness in both adults and juveniles and a summary of recent research regarding the relationship of mental illness to violence.     

Short-term memory for responses: the "choose-small" effect

Pigeons' short-term memory for fixed-ratio requirements was assessed using a delayed symbolic matching-to-sample procedure. Different choices were reinforced after fixed-ratio 10 and fixed-ratio 40 requirements, and delays of 0, 5, or 20 s were sometimes placed between sample ratios and choice. All birds made disproportionate numbers of responses to the small-ratio choice alternative when delays were interposed between ratios and choice, and this bias increased as a function of delay. Preference for the small fixed-ratio alternative was also observed on "no-sample" trials, during which the choice alternatives were presented without a prior sample ratio. This "choose-small" bias is analogous to results obtained by Spetch and Wilkie (1983) with event duration as the discriminative stimulus. The choose-small bias was attenuated when the houselight was turned on during delays, but overall accuracy was not influenced systematically by the houselight manipulation.     

The analysis of structural equation models by means of derivative free nonlinear least squares

It is shown that the PAR Derivative-Free Nonlinear Regression program in BMDP can be used to fit structural equation models, producing generalized least squares estimates, standard errors, and goodness-of-fit test statistics. Covariance structure models more general than LISREL can be analyzed. The approach is particularly useful for dealing with new non-standard models and experimenting with alternate methods of estimation. The research of the second author was supported by the NSF grant MCS 83-01587. We wish to thank our referees for some very valuable suggestions.     

Best linear prediction of composite universe scores

The problem of predicting universe scores for samples of examinees based on their responses to samples of items is treated. A general measurement procedure is described in which multiple test forms are developed from a table of specifications and each form is administered to a different sample of examinees. The measurement model categorizes items according to the cells of such a table, and the linear function derived for minimizing error variance in prediction uses responses to these categories. In addition, some distinctions are drawn between aspects of the approach taken here and the familiar regressed score estimates.The author thanks Robert L. Brennan, Michael J. Kolen, and Richard Sawyer for helpful comments and corrections, and anonymous reviewers for suggested improvements.     

On the standard error of the modified biserial correlation

A paradoxical implication of Kraemer's expression for the large-sample standard error of Brogden's form of the biserial correlation is identified, and a new expression is given which does not imply the paradox. However, numerical evidence is presented which calls into question the correctness of the expression.     

Structural analysis of subjective categorical data

A general approach to the analysis of subjective categorical data is considered, in which agreement matrices of two or more raters are directly expressed in terms of error and agreement parameters. The method provides focused analyses of ratings from several raters for whom ratings have measurement error distributions that may induce bias in the evaluation of substantive questions of interest. Each rater's judgment process is modeled as a mixture of two components: an error variable that is unique for the rater in question as well as an agreement variable that operationalizes the true values of the units of observation. The statistical problems of identification, estimation, and testing of such measurement models are discussed.The general model is applied in several special cases. The most simple situation is that underlying Cohen's Kappa, where two raters place units into unordered categories. The model provides a generalization and systematization of the Kappa-idea to correct for agreement by chance. In applications with typical research designs, including a between-subjects design and a mixed within-subjects, between-subjects design, the model is shown to disentangle structural and measurement components of the observations, thereby controlling for possible confounding effects of systematic rater bias. Situations considered include the case of more than two raters as well as the case of ordered categories. The different analyses are illustrated by means of real data sets.The authors wish to thank Lawrence Hubert and Ivo Molenaar for helpful and detailed comments on a previous draft of this paper. Thanks are also due to Jens Möller und Bernd Strauß for the data from the 1992 Olympic Games. We thank the editor and three anonymous reviewers for valuable comments on an earlier draft.     

汉语句子格角色分配的一种神经网络方法

提出了一个基于分布式表征的计算模型,通过并行分布加工方式完成六类汉语句子的格角色分配任务。模型是一个四层的前传网络,包括输入层（词的分布式表征层）,两个隐层,输出层（格角色层）;其中第一隐层的一部分反馈到输入层。模型采用误差反传算法,通过提供学习样本和目标输出,不断调整三个权值矩阵,使得网络稳定时能得到正确的结果。经过训练后的网络具有一定的稳定性和鲁棒性。还对这种方法与传统的符号处理方法作了比较和分析。     

概化理论在作文评分中的应用研究

概化理论是现代心理测量理论之一,该文简要地介绍了该理论的基本思想并用此理论对作文评分的误差控制问题进行了应用性探讨。研究中请６位评分员对２０名学生每人三种文体的作文用分项评分法进行评定。然后用ＧＥＮＯＶＡ软件的估计了作文评分中的评分员效应和题目效应,并对各种误差构成进行了分析比较。结果表明：在作文评分中,评分员勺最大,题目效应不明显。同时还发现,不同文体对评分误差有重要影响。论文文的评分误差最大,