Performance of Linear Mixed Models in Estimating Structural Rates of Glaucoma Progression Using Varied Random Effect Distributions.

ABSTRACT:

Purpose

To compare how linear mixed models (LMMs) using Gaussian, Student t, and log-gamma (LG) random effect distributions estimate rates of structural loss in a glaucomatous population using OCT and to compare model performance to ordinary least squares (OLS) regression.

Design

Retrospective cohort study.

Subjects

Patients in the Bascom Palmer Glaucoma Repository (BPGR).

Methods

Eyes with ≥ 5 reliable peripapillary retinal nerve fiber layer (RNFL) OCT tests over ≥ 2 years were identified from the BPGR. Retinal nerve fiber layer thickness values from each reliable test (signal strength ≥ 7/10) and associated time points were collected. Data were modeled using OLS regression as well as LMMs using different random effect distributions. Predictive modeling

SUBMITTER: Swaminathan SS 

PROVIDER: S-EPMC10838913 | biostudies-literature | 2024 May-Jun

REPOSITORIES: biostudies-literature