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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 Dan McNeish, Ph.D.

Dynamic structural equation modeling (DSEM) is a recently developed analytic framework that combines aspects of multilevel modeling, structural equation modeling, and time-series analysis. Although DSEM has many applications, it is particularly useful for intensive longitudinal data.

Roughly speaking, longitudinal data is considered intensive if you have 15 or more repeated measures on the same individuals over a relatively short time span, such as a few days or weeks. This type of data has become increasingly common as technological advances like smartphones and wearables continue to transform how data are collected, how studies are designed, and what research questions can be asked.

While traditional longitudinal models focus on growth over longer durations, intensive longitudinal models focus on momentary changes over short durations. For instance, a growth model may be interested in how anxiety changes over 12 months, but an intensive longitudinal model may be interested in why anxiety was low at 12pm, spiked at 4pm and receded at 8pm.

In this seminar, you’ll learn about both foundational and intermediate topics in DSEM. The course will emphasize those capabilities of DSEM that distinguish it from more traditional methods for intensive longitudinal analysis, like mixed models or univariate time series. These capabilities include

• Modeling outcomes that are latent or based on measurement scales composed of multiple item responses.
• Estimating multivariate models for mediation (e.g., how chains of effects unfold over time).
• Dyadic data (e.g., how related individuals like romantic couples or managers/employees affect each other over time).

After completing this seminar, you’ll have a solid foundation in

• The differences between intensive longitudinal data and traditional longitudinal data.
• The opportunities and unique research questions that can be asked and answered with DSEM and intensive longitudinal data.
• The conceptual underpinnings of DSEM and how it can handle the special features of intensive longitudinal data.
• How to leverage concepts from multilevel and structural equation modeling to build models that capture idiosyncratic features of intensive longitudinal data and designs.