Oftentimes in many fields of the social and natural sciences, data are obtained within a nested structure (e.g., students within schools). To effectively analyze data with such a structure, multilevel models are frequently employed. The present study utilizes a Monte Carlo simulation to compare several novel multilevel classification algorithms…

Knowledge about the interior density distribution of a planetary body can constrain geophysical processes and reveal information about the origin and evolution of the body. Properties of this interior distribution can be inferred by analyzing gravity acceleration data sampled by orbiting satellites. Usually, the gravity data is complemented with…

Previous studies on Bayesian situations, in which probabilistic information is used to update the probability of a hypothesis, have often focused on the calculation of a posterior probability. We argue that for an in-depth understanding of Bayesian situations, it is (apart from mere calculation) also necessary to be able to evaluate the effect of…

Purpose: Although conversational recast treatment is generally efficacious, there are many ways in which the individual components of the treatment can be delivered. Some of these are known to enhance treatment, others appear to interfere with learning, and still others appear to have no impact at all. This study tests the potential effect of…

With the advent of technological advancement in learning, such as context-awareness, ubiquity and personalisation, various innovations in teaching and learning have led to improved learning. This research paper aims to develop a system that supports personalised learning through adaptive content, adaptive learning path and context awareness to…

Drug repurposing refers to the process of discovering new therapeutic uses for existing medicines. Compared to traditional drug discovery, drug repurposing is attractive for its speed, cost, and reduced risk of failure. However, existing approaches for drug repurposing involve complex, computationally-intensive analytical methods that are not…

In parallel process latent growth curve mediation models, the mediation pathways from treatment to the intercept or slope of outcome through the intercept or slope of mediator are often of interest. In this study, we developed causal mediation analysis methods for these mediation pathways. Particularly, we provided causal definitions and…

Mediation analysis is widely applied in various fields of science, such as psychology, epidemiology, and sociology. In practice, many psychological and behavioral phenomena are dynamic, and the corresponding mediation effects are expected to change over time. However, most existing mediation methods assume a static mediation effect over time,…

Mediation analysis is widely applied in various fields of science, such as psychology, epidemiology, and sociology. In practice, many psychological and behavioral phenomena are dynamic, and the corresponding mediation effects are expected to change over time. However, most existing mediation methods assume a static mediation effect over time,…

This study examined the false positive (FP) rates and sensitivity of Bayesian fit indices to structural misspecification in Bayesian structural equation modeling. The impact of measurement quality, sample size, model size, the magnitude of misspecified path effect, and the choice or prior on the performance of the fit indices was also…

Students' reading ability affects their outcomes in learning software even outside of reading education, such as in math education, which can result in unexpected and inequitable outcomes. We analyze an adaptive learning software using Bayesian Knowledge Tracing (BKT) to understand how the fairness of the software is impacted when reading ability…

A hallmark of effective teaching is that it grants learners not just a collection of facts about the world, but also a toolkit of abstractions that can be applied to solve new problems. How do humans teach abstractions from examples? Here, we applied Bayesian models of pedagogy to a necklace-building task where teachers create necklaces to teach a…

Previous psychophysical studies reported a positive aftereffect in tactile temporal order judgments, which can be explained by the Bayesian estimation model ('Bayesian calibration'). We investigated the relationship between Bayesian calibration and autistic traits in participants with typical development (TD) and autism spectrum disorder (ASD).…

Though individual categorization or decision processes have been studied separately in many previous investigations, few studies have investigated how they interact by using a two-stage task of first categorizing and then deciding. To address this issue, we investigated a categorization-decision task in two experiments. In both, participants were…

To evaluate multidimensional factor structure, a popular method that combines features of confirmatory and exploratory factor analysis is Bayesian structural equation modeling with small-variance normal priors (BSEM-N). This simulation study evaluated BSEM-N as a variable selection and parameter estimation tool in factor analysis with sparse…