A marginalization model for the multidimensional unfolding analysis of ranking data

A marginalization model for the multidimensional unfolding analysis of ranking data is presented. A subject samples one of a number of random points that are multivariate normally distributed. The subject perceives the distances from the point to all the stimulus points fixed in the same multidimensional space. The distances are error perturbed in this perception process. He/she produces a ranking dependent on these error-perturbed distances. The marginal probability of a ranking is obtained according to this ranking model and by integrating out the subject (ideal point) parameters, assuming the above distribution. One advantage of the model is that the individual differences are captured using the posterior probabilities of subject points. Three sets of ranking data are analyzed by the model.     

Application of the bootstrap methods in factor analysis

A Monte Carlo experiment is conducted to investigate the performance of the bootstrap methods in normal theory maximum likelihood factor analysis both when the distributional assumption is satisfied and unsatisfied. The parameters and their functions of interest include unrotated loadings, analytically rotated loadings, and unique variances. The results reveal that (a) bootstrap bias estimation performs sometimes poorly for factor loadings and nonstandardized unique variances; (b) bootstrap variance estimation performs well even when the distributional assumption is violated; (c) bootstrap confidence intervals based on the Studentized statistics are recommended; (d) if structural hypothesis about the population covariance matrix is taken into account then the bootstrap distribution of the normal theory likelihood ratio test statistic is close to the corresponding sampling distribution with slightly heavier right tail.This study was carried out in part under the ISM cooperative research program (91-ISM · CRP-85, 92-ISM · CRP-102). The authors would like to thank the editor and three reviewers for their helpful comments and suggestions which improved the quality of this paper considerably.     

大学生场依存性─－独立性认知方式分析

对二十一个学科专业１５２６名大学生的场依存性─－独立性认知方式进行调查所获得的新近常模资料表明：大学生场依存性─－独立性个体差异的群体分布是正态性的,其总体平均水平以《认知方式图形测验》成绩作指标为１３．７（ｓ为４．６）。在此基础上,对文献所报道的影响场依存性─－独立性发展水平的两个因素作了进一步的研究分析,发现,大学生场依存性─－独立性的性别差异非常接近显著水平;专业分化是不依赖于性别因素而导致大学生场依存性─－独立性水平显著不同的主要因素．     

Human Signal-detection Performance: Effects Of Signal Presentation Probabilities And Reinforcer Distributions

University students participated in one of four standard two-choice signal-detection experiments in which signal presentation probability was varied and the reinforcement distribution was held constant and equal. In Experiments 1, 3 and 4, subjects' performance showed a systematic response bias for reporting the stimulus presented least often. Experiments 1 and 4 showed that this effect was reliable with extended training and monetary, rather than point, reinforcement. In Experiment 2, all correct responses were signaled in some way, and this produced the opposite relationship between signal presentation probability and response bias. Experiments 1 and 3 found that explicitly deducting money (intended as punishment) for equal numbers of incorrect responses on each alternative, or varying the obtained overall rate of reinforcement, produced no clear change in response bias. The bias, shown by humans, for reporting the stimulus presented least often remains a challenge for theories of stimulus detection.     

Rasch's multiplicative poisson model with covariates

As a multivariate model of the number of events, Rasch's multiplicative Poisson model is extended such that the parameters for individuals in the prior gamma distribution have continuous covariates. The parameters for individuals are integrated out and the hyperparameters in the prior distribution are estimated by a numerical method separately from difficulty parameters that are treated as fixed parameters or random variables. In addition, a method is presented for estimating parameters in Rasch's model with missing values. The author is now affiliated with the Otara University of Commerce. The author is grateful to Yoshio Takane, Haruo Yanai, Eiji Muraki, the editor and referees for their careful readings and helpful suggestions on earlier versions of this paper. Part of this work was presented at the third European Congress of Psychology at Tampere, Finland in 1993.     

Temporal control of behavior: schedule interactions

In Experiment I the response that terminated the postreinforcement pauses occurring under a fixed-interval 60-second schedule was reinforced, if the pause duration exceeded 30 seconds. The percentage of such pauses, rather than increasing, decreased. There were complex effects on the discriminative control of the pause by the reinforcer terminating the previous fixed interval, depending on whether the fixed interval and the added reinforcer were the same or different. In Experiments II(a) and II(b), each reinforcement initiated an alternative fixed-interval interresponse-time-greater-than-t-sec schedule, the schedule values being systematically varied. When the response following a pause exceeding a given duration was reinforced, fewer such pauses occurred than when they were not reinforced, i.e., on the comparable simple fixed-interval schedule. There was no systematic relationship between mean interrinforcement interval and duration of the postreinforcement pause. The pause duration initiated by reinforcement was directly related to the dependency controlling the shortest pause at that time, regardless of changes in mean interreinforcement interval.     

A molar theory of reinforcement schedules

Behavior of subjects exposed to concurrent and individual interval and ratio schedules of reinforcement may be described in terms of a set of expressions relating the value of responses to their durations, a feedback equation relating reinforcement to response duration, and the assumption that subjects allocate their time among various responses so as to maximize value.     

Response strength in multiple periodic and aperiodic schedules

Responding in multiple periodic and aperiodic schedules of equal mean reinforcement rate was examined during extinction, satiation, and in the presence of various free-food schedules. In Experiments I and II, pigeons were trained on multiple variable-interval–fixed-interval schedules. Decreases in the rate of responding due to extinction, satiation, or food schedules were approximately equal regardless of the temporal pattern of reinforcer presentation. In Experiment III, pigeons responded on a two-component multiple schedule in which each component was a two-member homogeneous response chain terminating in a fixed-interval schedule during one component and in a variable-interval schedule during the other. The length of both terminal links was varied over a series of conditions. Initial-link responding in the fixed-interval component was reduced more by increasing terminal-link length than was initial-link responding in the variable-interval component. However, no differences in resistance to satiation and extinction were obtained across the fixed and variable components. If the relative decrease in responding produced by satiation and extinction is used as an index of the “value” of the conditions maintaining responding, then these data suggest that fixed and variable schedules of equal mean length are equally valued. This conclusion, however, is not consistent with findings of preference for variable over fixed schedules obtained in studies using concurrent-chain procedures.     

Alternative fixed-ratio fixed-interval schedules of reinforcement

Five rats were trained under alternative fixed-ratio fixed-interval schedules, in which food reinforcement was provided for the completion of either a fixed-ratio or a fixed-interval requirement, whichever was met first. Overall response rate and running rate (the rate of responding after the postreinforcement pause) decreased for all subjects as the fixed-ratio value increased. As the proportion of reinforcements obtained from the fixed-ratio component increased and the alternative schedule approached a simple fixed ratio, overall response rate and running rate both increased; conversely, as the proportion of reinforcements obtained from the fixed-interval component increased and the alternative schedule approached a simple fixed interval, response rates decreased. Postreinforcement pause length increased linearly as the average time between reinforcements increased, regardless of the schedule parameters. A break-run pattern of responding was predominant at low- and medium-valued fixed ratios. All subjects displayed at least occasional positively accelerated responding within interreinforcement intervals at higher fixed-ratio values.     

A stochastic model for test-retest correlations

A simple stochastic model is formulated in order to determine the optimal time between the first test and the second test when the test-retest method of assessing reliability is used. A forgetting process and a change in true score process are postulated. The optimal time between tests is derived by maximizing the probability that the respondent has not remembered the response on the first test and has not had a change in true score. The resulting test-retest correlation is then found to be a linear function of the true reliability of the test, where the slope of this function is the key probability of not remembering and having no change in true score. Some numerical examples and suggestions for using the results in empirical studies are given. Specific recommendations are presented for improved design and analysis of intentions data.This research was made possible by a grant from the Center for Food Policy Research, Graduate School of Business, Columbia University, New York, New York, 10027.