Estimation of Models in a Rasch Family for Polytomous Items and Multiple Latent Variables

The Rasch family of models considered in this paper includes models for polytomous items and multiple correlated latent traits, as well as for dichotomous items and a single latent variable. An R package is described that computes estimates of parameters and robust standard errors of a class of log-linear-by-linear association (LLLA) models, which are derived from a Rasch family of models. The LLLA models are special cases of log-linear models with bivariate interactions. Maximum likelihood estimation of LLLA models in this form is limited to relatively small problems; however, pseudo-likelihood estimation overcomes this limitation. Maximizing the pseudo-likelihood function is achieved by maximizing the likelihood of a single conditional multinomial logistic regression model. The parameter estimates are asymptotically normal and consistent. Based on our simulation studies, the pseudo-likelihood and maximum likelihood estimates of the parameters of LLLA models are nearly identical and the loss of efficiency is negligible. Recovery of parameters of Rasch models fit to simulated data is excellent.

Investigating Factors Affecting Students\u27 Satisfaction with Computer-based Assessment

Despite the increasing use of computer-based assessment (CBA), there remains a dearth of evidence of what factors contribute to students’ satisfaction with CBA. We investigated four factors that are extracted from the TIMSS 2019 (Trends in International Mathematics and Science Study) Student Questionnaire eTIMSS Supplement – which was designed to examine student’s experience with the computer version of TIMSS (Mullis, Martin, Foy, Kelly, & Fishbein (2020)). The four factors were perceived technical difficulties, frequency of computer or tablet usage at school, self-confidence in computer or tablet usage, and familiarity with information and communication technology (ICT) terminology

Robust optimization method of emergency resource allocation for risk management in inland waterways

This study proposes a robust optimization method for waterborne emergency resource allocation in inland waterways that addresses the uncertainties and mismatches between supply and demand. To accomplish this, we integrate the risk evaluation of maritime with a robust optimization model and employ the Entropy Weighted Method (EWM)-Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-Analytic Hierarchy Process (AHP) method to evaluate the risk of various areas. The approach enables exploration of the relationship between maritime risk and emergency resource allocation strategy. The robust optimization method is used to deal with uncertainty and derive the robust counterpart of the proposed model. We establish an emergency resource allocation model that considers both the economy and timeliness of emergency resource allocation. We construct an optimization model and transform it into an easily solvable robust counterpart model. The results demonstrate that the proposed method can adapt to real-world scenarios, and effectively optimize the configuration effect while improving rescue efficiency under reasonable resource allocation. Specifically, the proportion of rescue time saved ranges from 28.52% to 92.60%, and the proportion of total cost saved is 95.82%. Our approach has significant potential to provide a valuable reference for decision-making related to emergency resource allocation in maritime management

Estimation of Models in a Rasch Family for Polytomous Items and Multiple Latent Variables

The Rasch family of models considered in this paper includes models for polytomous items and multiple correlated latent traits, as well as for dichotomous items and a single latent variable. An R package is described that computes estimates of parameters and robust standard errors of a class of log-linear-by-linear association (LLLA) models, which are derived from a Rasch family of models. The LLLA models are special cases of log-linear models with bivariate interactions. Maximum likelihood estimation of LLLA models in this form is limited to relatively small problems; however, pseudo-likelihood estimation overcomes this limitation. Maximizing the pseudo-likelihood function is achieved by maximizing the likelihood of a single conditional multinomial logistic regression model. The parameter estimates are asymptotically normal and consistent. Based on our simulation studies, the pseudo-likelihood and maximum likelihood estimates of the parameters of LLLA models are nearly identical and the loss of efficiency is negligible. Recovery of parameters of Rasch models fit to simulated data is excellent

Loglinear Models as Item Response Models

For analyzing item response data, item response theory (IRT) models treat the discrete responses to the items as driven by underlying continuous latent traits, and consider the form of conditional probability of the response to each item given the latent traits. In a similar fashion, log-linear models directly consider the form of the manifest probability of response patterns. Researchers have been connecting the two paradigms by establishing equivalence relationships between IRT models and log-linear models. This has lead to the notion of obtaining IRT solutions by fitting their equivalent log-linear models. In this research, I have established a family of log-linear models, log linear-by-linear association (LLLA) models, that incorporate a variety of IRT models, particularly, a family of generalized Rasch models. I have derived an extension of the Dutch Identity theorem to polytomous items and utilized it to develop the models that incorporate item covariates and person covariates. Noteworthy features of the models include both polytomous responses and multiple latent traits. Along with developing this new family of models, I have conducted extensive research on the development of an accompanying estimation method. Historically, a significant barrier to the application of log-linear models in analyzing item responses has been the high computational cost of maximum likelihood estimation (MLE), due to the fact that the number of response patterns grows exponentially as the number of items increases. To solve this computational problem, a pseudo-likelihood estimation (PLE) method is proposed and it dramatically decreases the computational cost. To demonstrate the effectiveness of the developed models and the pseudolikelihood estimation method, I will present results of a series of simulation studies. To demonstrate the practical advantages of the methods, I will give a detailed description of an application to a real data set from a study on verbally aggressive behavior

X-ray and EPR studies of strong intermolecular sickle hemoglobin contacts.

X-ray and EPR studies of strong intermolecular sickle hemoglobin contacts

Effects of Pipe Roof Support and Grouting Pre-Reinforcement on the Track Settlement

Based on the first shallow tunnel passing below an active railway station in the loess area in China, studies on the tunnel deformation and track settlement during tunneling are performed by using FLAC3D. It is found that, without adopting other reinforcement measures, the maximum track settlement has far exceeded engineering requirements. To reduce deformations induced by the tunneling, the combined presupport technique of the pipe roof and grouting reinforcement is presented and optimal construction parameters are provided. It is concluded that the installation of the pipe roof support plays an important role in controlling tunnel crown settlement and track settlement. The optimal pipe diameter is 159 mm, and the optimal arrangement area of the pipe roof is 150°. Grouting could improve soil strength and reduce deformations. The optimal thickness of the grouting reinforcement ring is 2 m. When the optimal parameters of the combined presupport technique are adopted, calculation results show that the maximum track settlement would reach 13.8 mm, which realized the settlement control goal of a maximum value of 15 mm. At last, the combined presupport technique proposed has been well validated in the “Railway Station” of Metro Line 4

X-ray and EPR studies of strong intermolecular sickle hemoglobin contacts.

X-ray and EPR studies of strong intermolecular sickle hemoglobin contacts