Integrating Factor Analysis with the Cox Proportional Hazards Model for Neonatal Mortality Analysis Using KDHS 2022 Data

Aims/Objectives: To integrate Exploratory Factor Analysis (EFA) with Cox proportional hazards regression to reduce multicollinearity among correlated covariates and identify neonatal mortality risk factors in Kenya. Study Design: Secondary analysis of a nationally representative cross-sectional demographic health survey, using a retrospective cohort (survival analysis) design. Place and Duration of Study: The Catholic University of Eastern Africa, using data from the 2022 Kenya Demographic and Health Survey (KDHS); analysis conducted between April 2026 and August 2026. Methodology: Data from 77,089 live births recorded in the 2022 KDHS were analyzed. Latent dimensions from correlated variables relating to socioeconomic status and fertility history were extracted. Resulting factor scores, together with selected observed covariates, were incorporated into a stratified Cox proportional hazards model. Five alternative model specifications were compared using Akaike and Bayesian Information Criteria, pseudo-R2, concordance index (C- index), events per variable, and generalized variance inflation factors.