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.     

Some neglected problems in IRT

The paper addresses three neglected questions from IRT. In section 1, the properties of the “measurement” of ability or trait parameters and item difficulty parameters in the Rasch model are discussed. It is shown that the solution to this problem is rather complex and depends both on general assumptions about properties of the item response functions and on assumptions about the available item universe. Section 2 deals with the measurement of individual change or “modifiability” based on a Rasch test. A conditional likelihood approach is presented that yields (a) an ML estimator of modifiability for given item parameters, (b) allows one to test hypotheses about change by means of a Clopper-Pearson confidence interval for the modifiability parameter, or (c) to estimate modifiability jointly with the item parameters. Uniqueness results for all three methods are also presented. In section 3, the Mantel-Haenszel method for detecting DIF is discussed under a novel perspective: What is the most general framework within which the Mantel-Haenszel method correctly detects DIF of a studied item? The answer is that this is a 2PL model where, however, all discrimination parameters are known and the studied item has the same discrimination in both populations. Since these requirements would hardly be satisfied in practical applications, the case of constant discrimination parameters, that is, the Rasch model, is the only realistic framework. A simple Pearsonx ² test for DIF of one studied item is proposed as an alternative to the Mantel-Haenszel test; moreover, this test is generalized to the case of two items simultaneously studied for DIF.     

Identification of inconsistent variates in factor analysis

When some of observed variates do not conform to the model under consideration, they will have a serious effect on the results of statistical analysis. In factor analysis the model with inconsistent variates may result in improper solutions. In this article a useful method for identifying a variate as inconsistent is proposed in factor analysis. The procedure is based on the likelihood principle. Several statistical properties such as the effect of misspecified hypotheses, the problem of multiple comparisons, and robustness to violation of distributional assumptions are investigated. The procedure is illustrated by some examples.     

Social reinforcement of operant behavior in rats: a methodological note.

An apparatus was developed to study social reinforcement in the rat. Four Long-Evans female rats were trained to press a lever via shaping, with the reinforcer being access to a castrated male rat. Responding under a fixed-ratio schedule and in extinction was also observed. Social access was found to be an effective reinforcer. When social reinforcement was compared with food reinforcement under similar conditions of deprivation and reinforcer duration, no significant differences were observed.     

Estimating the polyserial correlation coefficient

We develop simple noniterative estimators of the polyserial correlation coefficient. A general relationship between the polyserial correlation and the point polyserial correlation is exploited to give extensions of Pearson's, Brogden's, and Lord's biserial estimators to the multicategory setting. The small sample and asmptotic properties of these estimators are studied in some detail. A comparison with maximum likelihood estimates shows that Lord's polyserial estimator is fairly efficient across three probability models.The authors would like to thank the referees for suggestions that improved the presentation of the paper.     

韦伯比的拟合公式

本文以神经生理学为基础,结合感官具有调节和比较两功能的实用性,建立起刺激在大脑皮层上引起感知效应Ｅ的数学模型：Ｅ＝Ｂｌｏｇ（１＋ｋＩ）,其中ｋ＝Ｉ￣（－ｂ）／ａ。从此出发,可推出中等以上刺激的差别阈判据：△ＥＭ＝恒量。将此判据推广到弱刺激,即得到差别阈的普适规律：△Ｉ／（Ｉ＋ａＩ￣ｂ）＝Ｎ,亦即韦伯定律的修订公式。从弱到强的广大刺激范围内,它都能与实验数据拟合良好。     

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.     

Delayed reinforcement of fixed-ratio performance without mediating exteroceptive conditioned reinforcement

The performance of pigeons was studied under conditions in which the completion of a fixed-ratio requirement was not contiguous with the presentation of a reinforcer. Timein and timeout periods alternated throughout the experimental sessions. Responses made by an experimental bird during the timein period were accumulated, and when a fixed-ratio requirement had been met, grain was presented to the experimental bird and a yoked control following their first response in the next timein period. Across most manipulations of the fixed-ratio requirement and of the duration of the timeout period, the response rates of the experimental birds were considerably higher than those of their controls, suggesting that the response-reinforcer dependency controlled the behavior of the experimental bird in the absence of a close temporal association between responding on the ratio schedule and reinforcer presentations.     

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.