Event Phone: 1-610-715-0115

Cancellation Policy: If you cancel your registration at least two weeks before the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50).

In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.

A 4-Day Livestream Seminar Taught by Matthew Diemer, Ph.D.

Psychometrics is the science of how we measure the psychological attributes of people. These attributes include abilities, aptitudes, achievement, attitudes, interests, personality traits, cognitive functioning, and mental health.

The theoretically-informed and precise measurement of such latent phenomena is an essential component of many of the things we hold dear. These include scientific advances (e.g., can I make a claim that I am measuring what I purport to measure?), educational placement decisions (e.g., should a child be placed into a gifted program?), statistical power (e.g., is my measure precise enough to suggest that X predicts Y?), and other key considerations.

This seminar emphasizes the conceptual understanding and application of psychometric principles. These techniques provide a powerful way to identify and remediate bias in measurement, as well as to make equity-informed claims in the language of psychometrics.

The seminar centers on latent variables as an overarching perspective to understand psychometric concepts, principles, and techniques. Simply put, a latent variable is something unobserved, or not directly measurable, that is of interest (e.g., achievement, well-being, motivation, racial identity). Psychometricians use directly observable measures (e.g., items, subscales, physiological measures) to model the underlying latent constructs of interest.

Conceptually, the core of psychometrics is about using empirical evidence to make claims in support of construct validity, generally regarded as the most central aspect of validity. This evidence can be obtained with key analytic approaches that are covered in this workshop. Specifically, (a) exploratory factor analyses (EFA), (b) confirmatory factor analyses (CFA), (c) MIMIC models, and (d) measurement invariance testing. Importantly, these last two approaches provide powerful strategies to detect and remediate measurement bias, as well as to support claims about whether measures mean the same thing and can be measured in the same way across groups.