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.

When markets fall down: are emerging markets all the same?

This paper studies the dynamics of stock market regimes in emerging markets. Using a mixture version of the standard regime-switching model, we find that the 18 analysed emerging markets can be clustered into three groups. Whereas each of these three groups is characterized by the same two regimes-a bull state with positive returns and low volatility and a bear state with negative returns and high volatility-they clearly differ with respect to their regime-switching dynamics. The first group contains stock markets which swing frequently between the two regimes, the second group shows more regime persistence, and the third group consists of stock markets that are less likely than the others to move to a bear regime period. Standard practice among stock market analysts is to group emerging markets by geographical region. The fact that our model-based clustering is only weakly related to such a regional classification demonstrates the limited validity of the latter. Moreover, a detailed analysis of regime synchronicities across the 18 studied emerging markets shows that there is evidence of regime synchronicity for certain pairs of markets, but this does not rule out that two synchronized markets have different regime dynamics and thus belong to different regime-switching clusters. Hence, our results show that it is incorrect to treat the studied emerging markets as a single homogeneous group because there is strong evidence for substantial differences in their regime-switching dynamics.info:eu-repo/semantics/acceptedVersio

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

A new three-step method for using inverse propensity weighting with latent class analysis

Bias-adjusted three-step latent class analysis (LCA) is widely popular to relate covariates to class membership. However, if the causal effect of a treatment on class membership is of interest and only observational data is available, causal inference techniques such as inverse propensity weighting (IPW) need to be used. In this article, we extend the bias-adjusted three-step LCA to incorporate IPW. This approach separates the estimation of the measurement model from the estimation of the treatment effect using IPW only for the later step. Compared to previous methods, this solves several conceptual issues and more easily facilitates model selection and the use of multiple imputation. This new approach, implemented in the software Latent GOLD, is evaluated in a simulation study and its use is illustrated using data of prostate cancer patients

Students’ experiences with challenge-based learning at TU/e innovation Space:overview of five key characteristics across a broad range of courses

Challenge-based learning (CBL) has emerged in the last decade as a response to the complexity of problems faced by modern society, new competencies needed for the workplace, and insights from cognitive sciences on knowledge acquisition and learner motivation. In CBL, students work on real-world problems which are open-ended and require interdisciplinary knowledge and entrepreneurial mindset. In the last three years, over 70 CBL experiments have been initiated at Eindhoven University of Technology (TU/e), in order to develop a broad range of CBL teaching practices. Half of these courses have taken place at TU/e innovation Space, which is a learning hub and expertise centre for CBL and entrepreneurship education. We use students’ evaluation surveys to analyse the experiences of Bachelor and Masters students in these courses. In particular, we are focusing on responses to five key course design characteristics set by the teaching staff as important: how interdisciplinary and challenge-based (or linked to real-life problems) the courses are, how entrepreneurial and hands-on they are, and how much they contributed to students’ personal development, as well as their team development. The results show that what attracts students to these CBL courses matches closely these five characteristics, and we discuss why this might be the case. Interestingly, some of the more hands-on aspects of the courses do not seem to have been affected by the COVID-19 disruption in the 2019-2020 academic year

A cross-cultural comparison of student learning patterns in higher education

Marambe, K. N., Vermunt, J. D., & Boshuizen, H. P. A. (2012). A cross-cultural comparison of student learning patterns in higher education. Higher Education, 64(3), 299-316. doi:10.1007/s10734-011-9494-zThe aim of this study was to compare student learning patterns in higher education across different cultures. A meta-analysis was performed on three large-scale studies that had used the same research instrument: the Inventory of learning Styles (ILS). The studies were conducted in the two Asian countries Sri Lanka and Indonesia and the European country The Netherlands. Students reported use of learning strategies, metacognitive strategies, conceptions of learning and learning orientations were compared in two ways: by analyses of variance of students' mean scale scores on ILS scales, as well as by comparing the factor structures of the ILS-scales between the three studies. Results showed most differences in student learning patterns between Asian and European students. However, many differences were identified between students from the two Asian countries as well. The Asian learner turned out to be a myth. Moreover, Sri Lankan students made the least use of memorising strategies of all groups. That Asian learners would have a propensity for rote learning turned out to be a myth as well. Some patterns of learning turned out to be universal and occurred in all groups, other patterns were found only among the Asian or the European students. The findings are discussed in terms of learning environment and culture as explanatory factors. Practical implications for student mobility in an international context are derived

Understanding Filipino rice farmer preference heterogeneity for varietal trait improvements: A latent class analysis

Using an experimental methodology based on investment games, we examine whether smallholder rice farmers from Nueva Ecija, Philippines have heterogeneous preferences for improvements in 10 rice varietal traits. We use a latent class cluster approach to identify different segments of rice producing households and their distinct preferences for trait improvements. These clusters were characterised post hoc using household, farm, and marketing characteristics. On average, farmers invested the most in rice varietal trait improvements that offered opportunities to reduce losses caused by lodging, insects and diseases. We found four classes of farmers with distinct preferences for improvements in variety traits. The clusters were significantly different in terms of household and farm characteristics. These findings can guide breeding research in the development of varieties that have the traits farmers identified for improvement, and that will address the unique needs of distinct farmer segments.Rio Maligalig, Matty Demont, Wendy J. Umberger and Alexandra Peralt

Monitorial citizens or civic omnivores? Repertoires of civic participation among university students

In present-day societies, the extent to which young people still participate in civic life is an important matter of concern. The claim of a generational "decline" in civic engagement has been contested, and interchanged with the notion of a "replacement" of traditional engagement by new types of participation, and the emergence of the "monitorial citizen" who participates in more individualized ways. Concurrently, this study explored the assumption of a "pluralization" of involvement, advancing a new concept: the "civic omnivore," characterized by an expanded civic repertoire. Drawing data from a sample of 1,493 Belgian and Dutch university students, we identify five repertoires of participation such as, disengaged students, classical volunteers, humanitarian citizens, monitorial citizens, and civic omnivores. Our findings support the pluralization thesis, by showing that young citizens are not exclusively engaged in new monitorial ways, yet also expand their civic repertoire by combining traditional and new forms in more complex ways

Return to work trajectories among employees with mental health problems:Insights from longitudinal sickness absence data and a multi-stakeholder expert meeting

IOSH, the Chartered body for health and safety professionals, is committed to evidence-based practice in workplace safety and health. We maintain a Research Fund to support research and inspire innovation as part of our work as a thought leader in health and safet