Webinar Series

Psychometric Society Webinar Series

Overview

The Psychometric Society sponsors monthly seminars on contemporary topics in psychometrics that are broadly applicable and substantially impact practice.

Registration is free and requires clicking on a link near the bottom of each seminar’s webpage. Recordings of each seminar will be made available to Psychometric Society members under the membership portal.

Event

Psychometric Society Webinar Series

Modeling Heterogeneous Time Series from Multiple Individuals

The word "webinar" approximated with Greek alphabet.

Presenters: Zachary Fisher (Penn State University)

Data rising from high-dimensional time-dependent systems is increasingly common in the health, social and behavioral sciences. Despite the many benefits these data provide, relatively little work has been done to explicitly address the strong heterogeneity present in many processes involving human behavior. To address this gap in the literature, I will present the multi-VAR framework, a recently developed approach for modeling heterogeneous time-series data arising from multiple individuals.

Event

Psychometric Society Webinar Series

Online Calibration Designs and Methods for Multidimensional Computerized Adaptive Testing

Presenters: Ping Chen (Beijing Normal University), Chun Wang (University of Washington)

Computerized adaptive testing (CAT), as the earliest form of instantiation of artificial intelligence in assessment design, has been widely used in the fields of psychological testing, educational evaluation, personnel selection, and medical diagnosis. The continuous implementation and sustainable use of CAT rely heavily on periodical update and replenishment of the item bank.

Event

Psychometric Society Webinar Series

The Boltzmann Machine in Psychometrics: Implications and Applications

Presenters: Benjamin Deonovic (Corteva), Timo Bechger (Metior Consulting), Gunter Maris (Metior Consulting)

The Boltzmann machine remains an attractive generative model for supervised and unsupervised learning of complex multivariate distributions of binary random variables. Often the observed variables are augmented with unobserved binary variables and a Boltzmann machine is assumed for both together. Popular examples are restricted Boltzmann machines, latent tree models, and deep Boltzmann machines.

Event

Psychometric Society Webinar Series

Bayesian covariance structure modelling for measurement invariance testing

Presenter: Jean-Paul Fox, University of Twente

Bayesian covariance structure modeling (BCSM) is a new approach for modeling clustered data. In this multivariate modeling approach a dependence structure is directly modeled through a structured covariance matrix. The BCSM can be used to model measurement (in)variance, which shows to have many advantages over traditional methods.

Event

Psychometric Society Webinar Series

Computational psychometrics for test development: Combining language and psychometric modeling

Presenters: Yigal Attali, Andrew Runge, Geoff LaFlair, Kevin Yancey & Alina A. von Davier

Moderator: Peter Halpin

Along with the advances in communication and platform technology, it’s become apparent that (quality) content development is at the core of many industries, including the education industry. The development of learning and assessment content has been a craft that has required a high level of expertise, often of the type that was built over the years on the job. In the fast-paced digital education this is difficult to sustain.

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