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Friday, January 12
Fri, Jan 12, 8:30 AM - 10:15 AM
Crystal Ballroom B
Clinical Outcome Assessment (COA)

Latent trait shared parameter mixed-models for missing ecological momentary assessment data (304130)

*John Cursio, University of Chicago 

Keywords: ecological momentary assessment, missingness, ordinal outcomes

Latent trait shared parameter mixed-models (LTSPMM) for missing Ecological Momentary Assessment (EMA) data are developed in which data are collected in an intermittent fashion. Using Item Response Theory (IRT) models, a latent trait is used to model the missingness mechanism and modeled jointly with a mixed-model for longitudinal ordinal outcomes. Both one- and two-parameter LTSPMM are presented. These new models offer a unique way to analyze EMA data with many unique response patterns that cannot easily formed into latent classes. Previously, these LTSPMM were used with normal outcomes, and here ordinal models are estimated and compared. Item intercept and discrimination parameters, latent traits, and mixed-model covariates will be shown using both model types. Also, a discussion of model estimation issues will be presented for the ordinal LTSPMM.