Graphical regression models for polytomous variables

When modeling the relationship between two nominal categorical variables, it is often desirable to include covariates to understand how individuals differ in their response behavior. Typically, however, not all the relevant covariates are available, with the result that the measured variables cannot fully account for the associations between the nominal variables. Under the assumption that the observed and unobserved variables follow a homogeneous conditional Gaussian distribution, this paper proposesRC(M) regression models to decompose the residual associations between the polytomous variables. Based on Goodman's (1979, 1985)RC(M) association model, a distinctive feature ofRC(M) regression models is that they facilitate the joint estimation of effects due to manifest and omitted (continuous) variables without requiring numerical integration. TheRC(M) regression models are illustrated using data from the High School and Beyond study (Tatsuoka & Lohnes, 1988). This article was accepted for publication, when Willem J. Heiser was the Editor ofPsychometrika. This research was supported by grants from the National Science Foundation (#SBR96-17510 and #SBR94-09531) and the Bureau of Educational Research at the University of Illinois. We thank Jee-Seon Kim for comments and computational assistance.     

A violation of dominance and the consumption value of gambling

We document an apparently widespread violation of dominance in the horse‐racing betting market in the UK, and use the systematic variation in the incidence of this violation to estimate the consumption value of gambling. Betting‐shop gamblers in the UK face a tax on gambling of 10%, but have the choice of paying the tax either at the time of wager or on any return on a successful bet. It can be shown, however, that the latter act is strictly dominated by another action in which tax is paid on the wager. Despite this, more than 18% of bets appear to be placed by gamblers who choose to pay tax on the return. We explore the hypothesis that this apparent violation of rationality may be explained by a component of utility which represents the consumption value of gambling, which in turn varies with the amount wagered. We then estimate this component from a dataset consisting of a record of 25,000 individual bets using probit analysis of the tax decision. Copyright © 1999 John Wiley & Sons, Ltd.     

Dynamic estimation in the extended marginal Rasch model with an application to mathematical computer-adaptive practice

We introduce a general response model that allows for several simple restrictions, resulting in other models such as the extended Rasch model. For the extended Rasch model, a dynamic Bayesian estimation procedure is provided, which is able to deal with data sets that change over time, and possibly include many missing values. To ensure comparability over time, a data augmentation method is used, which provides an augmented person-by-item data matrix and reproduces the sufficient statistics of the complete data matrix. Hence, longitudinal comparisons can be easily made based on simple summaries, such as proportion correct, sum score, etc. As an illustration of the method, an example is provided using data from a computer-adaptive practice mathematical environment.     

Individual differences in sensory integration predict differences in time perception and individual levels of schizotypy

To interact functionally with our environment, our perception must locate events in time, including discerning whether sensory events are simultaneous. The Temporal Binding Window (TBW; the time window within which two stimuli tend to be integrated into one event) has been shown to relate to individual differences in perception, including schizotypy, but the relationship with subjective estimates of duration is unclear. We compare individual TBWs with individual differences in the filled duration illusion, exploiting differences in perception between empty and filled durations (the latter typically being perceived as longer). Schizotypy has been related to both these measures and is included to explore a potential link between these tasks and enduring perceptual differences. Results suggest that individuals with a narrower TBW make longer estimates for empty durations and demonstrate less variability in both conditions. Exploratory analysis of schizotypy data suggests a relationship with the TBW but is inconclusive regarding time perception.     

A two-fold transformation model for human action recognition using decisive pose

Human action recognition in videos is a tough task due to the complex background, geometrical transformation and an enormous volume of data. Hence, to address these issues, an effective algorithm is developed, which can identify human action in videos using a single decisive pose. To achieve the task, a decisive pose is extracted using optical flow, and further, feature extraction is done via a two-fold transformation of wavelet. The two-fold transformation is done via Gabor Wavelet Transform (GWT) and Ridgelet Transform (RT). The GWT produces a feature vector by calculating first-order statistics values of different scale and orientations of an input pose, which have robustness against translation, scaling and rotation. The orientation-dependent shape characteristics of human action are computed using RT. The fusion of these features gives a robust unified algorithm. The effectiveness of the algorithm is measured on four publicly datasets i.e. KTH, Weizmann, Ballet Movement, and UT Interaction and accuracy reported on these datasets are 96.66%, 96%, 92.75% and 100%, respectively. The comparison of accuracies with similar state-of-the-arts shows superior performance.     

The effects of intertrial interval and instructional format on skill acquisition and maintenance for children with autism spectrum disorders

We replicated and extended the study by Koegel, Dunlap, and Dyer (1980) by examining the effects of 3 intertrial‐interval (ITI) durations on skill acquisition in 2 children with autism spectrum disorders. Specifically, we compared the effect of short (2 s), progressive (2 s to 20 s), and long (20 s) ITIs on participants’ mastery of tacts or intraverbals presented in massed‐trial and varied‐trial instructional formats. We also measured (a) stereotypic and problem behavior during the ITI, (b) maintenance of skills, and (c) responding to novel adults and settings. Results showed that short ITIs in a varied‐trial format produced the most efficient acquisition of skills; however, most ITI durations produced more efficient skill acquisition in a varied format compared to a massed format. The trial format and ITI duration associated with the lowest levels of stereotypic and problem behavior during the ITI and responding during maintenance and novel adult and setting probes differed across participants.     

Step changes in the intertrial interval in the midsession reversal task: Predicting pigeons' performance with the learning-to-time model

Our goal was to assess the role of timing in pigeons' performance in the midsession reversal task. In discrete-trial sessions, pigeons learned to discriminate between 2 stimuli, S1 and S2. Choices of S1 were reinforced only in the first half of the session and choices of S2 were reinforced only in the second half. Typically, pigeons choose S2 before the contingency reverses (anticipatory errors) and S1 after (perseverative errors), suggesting that they time the interval from the beginning of the session to the contingency reversal. To test this hypothesis, we exposed pigeons to a midsession reversal task and, depending on the group, either increased or decreased the ITI duration. We then contrasted the pigeons' performance with the predictions of the Learning-to-Time (LeT) model: In both conditions, preference was expected to reverse at the same time as in the previous sessions. When the ITI was doubled, pigeons' preference reversal occurred at half the trial number but at the same time as in the previous sessions. When the ITI was halved, pigeons' preference reversal occurred at a later trial but at an earlier time than in the previous sessions. Hence, pigeons' performance was only partially consistent with the predictions of LeT, suggesting that besides timing, other sources of control, such as the outcome of previous trials, seem to influence choice.     

A semiparametric approach for item response function estimation to detect item misfit

When scaling data using item response theory, valid statements based on the measurement model are only permissible if the model fits the data. Most item fit statistics used to assess the fit between observed item responses and the item responses predicted by the measurement model show significant weaknesses, such as the dependence of fit statistics on sample size and number of items. In order to assess the size of misfit and to thus use the fit statistic as an effect size, dependencies on properties of the data set are undesirable. The present study describes a new approach and empirically tests it for consistency. We developed an estimator of the distance between the predicted item response functions (IRFs) and the true IRFs by semiparametric adaptation of IRFs. For the semiparametric adaptation, the approach of extended basis functions due to Ramsay and Silverman (2005) is used. The IRF is defined as the sum of a linear term and a more flexible term constructed via basis function expansions. The group lasso method is applied as a regularization of the flexible term, and determines whether all parameters of the basis functions are fixed at zero or freely estimated. Thus, the method serves as a selection criterion for items that should be adjusted semiparametrically. The distance between the predicted and semiparametrically adjusted IRF of misfitting items can then be determined by describing the fitting items by the parametric form of the IRF and the misfitting items by the semiparametric approach. In a simulation study, we demonstrated that the proposed method delivers satisfactory results in large samples (i.e., N ≥ 1,000).     

Effects of pre-operant running and sucrose concentration on operant wheel running on a fixed interval schedule of reinforcement

Prior research proposed that temporal control over the pattern of operant wheel running on a fixed interval (FI) schedule of sucrose reinforcement is a function of automatic reinforcement generated by wheel running and the experimentally arranged sucrose reinforcement. Two experiments were conducted to assess this prediction. In the first experiment, rats ran for different durations (0, 30, 60, and 180 min) prior to a session of operant wheel running on a FI 120-s schedule. In the second experiment, the concentration of sucrose reinforcement on a FI 180-s schedule was varied across values of 0, 5, 15, and 25%. In Experiment 1, as the duration of pre-operant running increased, the postreinforcement pause before initiation of running lengthened while wheel revolutions in the latter part of the FI interval increased. In Experiment 2, wheel revolutions markedly increased then decreased to a plateau early in the FI interval. Neither manipulation increased temporal control of the pattern of wheel running. Instead, results indicate that operant wheel running is regulated by automatic reinforcement generated by wheel activity and an adjunctive pattern of running induced by the temporal presentation of sucrose. Furthermore, the findings question whether the sucrose contingency regulates wheel running as a reinforcing consequence.