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LIMBARE: An Advanced Linear Mixed-Effects Breakpoint Analysis With Robust Estimation Method With Applications to
TingFang Lee1,2, Joel S Schuman1,3,4,5, Maria de Los Angeles Ramos Cadena1
1Department of Ophthalmology, NYU Langone Health, New York, NY, USA.
Translational Vision Science & Technology
|January 19, 2024
Summary
LIMBARE, a new method for longitudinal ophthalmic studies, accurately detects breakpoints in nonlinear associations. This advanced linear mixed-effects analysis with robust estimation outperforms other methods, especially with outlier data.
Area of Science:
- Ophthalmology
- Biostatistics
- Longitudinal Data Analysis
Background:
- Broken stick analysis is used to find nonlinear associations.
- Longitudinal ophthalmic studies require methods that handle repeated measures and outliers.
Purpose of the Study:
- To introduce LIMBARE, an advanced linear mixed-effects breakpoint analysis with robust estimation for longitudinal ophthalmic studies.
- To assess LIMBARE's performance in detecting breakpoints and handling outliers.
Main Methods:
- LIMBARE model setup and breakpoint estimation algorithm were detailed.
- Performance was evaluated using simulations and a longitudinal ophthalmic study (216 eyes, 3.7 years average follow-up).
Main Results:
- LIMBARE demonstrated minimal bias and mean squared error in breakpoint estimation.
- It provided the most accurate confidence interval coverage, even with outliers.
- LIMBARE identified more breakpoints in ophthalmic data compared to cross-sectional methods.
Conclusions:
- LIMBARE significantly improves breakpoint estimation accuracy in longitudinal ophthalmology.
- Cross-sectional analysis is not recommended for such studies.
- The LIMBARE R package offers a valuable tool for ophthalmic research.
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