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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 3-Day Livestream Seminar Taught by Kenneth A. Bollen, Ph.D.

With the growing availability of longitudinal data, researchers are inevitably confronted with the challenge of choosing an appropriate model. The range of possibilities is enormous. In an ideal world, theory and substantive arguments would be sufficiently clear to dictate a single, best model. But in practice, there is usually little guidance and much confusion. Often, researchers find themselves limited by conventional models and trends that are specific to their field, potentially missing out on more effective alternatives.

This seminar is designed to break those boundaries. It will teach and illustrate empirical methods for comparing and selecting the most suitable longitudinal models. Building on a structural equation modeling framework, it will introduce autoregressive models, random and fixed effects, latent growth curve models, and the autoregressive latent trajectory (ALT) model.

You’ll then learn how these and other models can be embedded in a general latent variable ALT (LV-ALT) model. This approach not only streamlines the selection of an appropriate longitudinal model but also enhances your ability to interpret and communicate the results from complex models with confidence.

The course begins by guiding you through the process of fitting multiple models to repeated measures for a single variable. The emphasis will be on practical skills like model estimation, assessing model fit, and comparing different models against the same data set. We then broaden the scope to the analysis of repeated measures for two or more variables, using detailed empirical examples to bring the theory to life.

Whether you’re a seasoned researcher or new to the field of longitudinal data analysis, this seminar offers invaluable insights and practical skills to elevate your research, taught by one of the giants of the field.