Ordinal Outcome State-Space Models for Intensive Longitudinal Data.

ABSTRACT: Intensive longitudinal (IL) data are increasingly prevalent in psychological science, coinciding with technological advancements that make it simple to deploy study designs such as daily diary and ecological momentary assessments. IL data are characterized by a rapid rate of data collection (1+ collections per day), over a period of time, allowing for the capture of the dynamics that underlie psychological and behavioral processes. One powerful framework for analyzing IL data is state-space modeling, where observed variables are considered measurements for underlying states (i.e., latent variables) that change together over time. However, state-space modeling has typically relied on continuous measurements, whereas psychological data often come in the form of ordinal measurements such as L

SUBMITTER: Henry TR 

PROVIDER: S-EPMC11582181 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature