Research project
Hybrid PCA and Factor Analysis for Clinical Predictive Models
Does combining principal component analysis with factor analysis improve stability in healthcare prediction without losing interpretability?
- Kind
- Research project
- Year
- 2022
- Status
- Complete
01
Abstract
Work on feature reduction for medical predictive modelling, where the number of correlated measurements is high, sample sizes are limited, and a model nobody can interpret will not be used regardless of its accuracy. The project compared a hybrid reduction approach against each method alone, measuring both predictive stability across resamples and how well the resulting components mapped to clinically meaningful structure.
02
Methods
- Principal component analysis
- Factor analysis
- Cross validation
- Statistical modelling