Overview
Nan M. Laird is a biostatistician (Harvard School of Public Health), one of the most influential figures in the statistics of longitudinal and incomplete data. She is a co-author of the foundational EM-algorithm paper (Dempster, Laird & Rubin 1977) and of the Laird–Ware linear mixed-effects model for longitudinal data (Laird & Ware 1982).
Key Contributions / Features
- Longitudinal categorical data (Fitzmaurice-Laird-Rotnitzky 1993): co-authored the review reconciling GEE and likelihood-based marginal models for repeated binary responses (Generalized Estimating Equations).
- EM algorithm (Dempster–Laird–Rubin 1977): maximum-likelihood estimation from incomplete data.
- Linear mixed-effects models (Laird–Ware 1982): the random-effects framework for continuous longitudinal data.
Related