Revealing hidden change through a response shift lens

Revealing hidden change through a response shift lens: The role of latent variable models

This webinar will focus on the role of latent variable models. Statistical methods using latent variable models are amongst the most popular approaches used for investigating response shift. However, the concept of latent variables is difficult to grasp and their application to analyses of response shift is rarely explicated in ways that are broadly accessible. Results from latent variable models are therefore easily misinterpreted. This webinar aims to bridge the gap between theoretical underpinnings of latent variable models and operationalizations of response shift. In doing so, attendees will gain a better understanding of response shift results from latent variable models, including structural equation models, item-response and Rasch measurement models, and latent variable mixture models.

Speakers:

• Mathilde Verdam, PhD, Research Associates, Department of Medical Psychology, Academic Medical Centre, Amsterdam UMC
• Véronique Sebille, PhD, Professor, SPHERE U1246 University of Nantes, France
• Rick Sawatzky, PhD RN, Professor in Nursing, Trinity Western University, Scientist, CHÉOS

Moderator:

• Richard Skolasky, ScD, Professor, Orthopaedic Surgery and Physical Medicine & Rehabilitation, Director, Spine Outcomes Research Center, Johns Hopkins University

Intended Audience:

• Anyone interested in measuring change over time using PROs
• Including researchers as knowledge users, clinicians, industry and regulating bodies, as well as new investigators

Level of Knowledge Needed:

• Intermediate

This webinar will provide the audience with:

• Insight to Response Shift methodology
• Statistical methods using latent variable models
• Response shift statistics

Learning Outcomes/Objectives:

• Expand understanding of response shift
• Include response shift focus in QOL studies