• Editorial

Re: 'Detecting patterns of occupational illness clustering with alternating logistic regressions applied to longitudinal data'

Citation

Chaix, B., Bobashev, G., Merlo, J., & Chauvin, P. (2004). Re: 'Detecting patterns of occupational illness clustering with alternating logistic regressions applied to longitudinal data'. American Journal of Epidemiology, 160(5), 505-506. DOI: 10.1093/aje/kwh216

Abstract

We read with interest the recently published article by Preisser et al. ( 1) on detecting patterns of occupational illness clustering with alternating logistic regressions. When investigations of variations in health or health-related behavior between areas are conducted, it is highly relevant to measure the extent to which phenomena occur in clusters. Furthermore, doing so is useful to determine whether area-level variations can be explained by a given set of individual- and area-level factors ( 2). Preisser et al. ( 1) discussed the relative strengths of alternating logistic regression and multilevel logistic models for measuring clustering of events. Indeed, it is important to compare the statistical consistency and interpretability of the different model-based indexes of clustering to determine which should be preferred in contextual analyses.
It is widely known that problems of …