Ashley Naimi
Ashley Naimi
Associate Professor, Department Epidemiology, Emory University
Verified email at - Homepage
Cited by
Cited by
An introduction to g methods
AI Naimi, SR Cole, EH Kennedy
International journal of epidemiology 46 (2), 756-762, 2017
Stacked generalization: an introduction to super learning
AI Naimi, LB Balzer
European journal of epidemiology 33, 459-464, 2018
The parametric g-formula for time-to-event data: intuition and a worked example
AP Keil, JK Edwards, DB Richardson, AI Naimi, SR Cole
Epidemiology 25 (6), 889-897, 2014
Constructing inverse probability weights for continuous exposures: a comparison of methods
AI Naimi, EEM Moodie, N Auger, JS Kaufman
Epidemiology 25 (2), 292-299, 2014
Reflection on modern methods: demystifying robust standard errors for epidemiologists
MA Mansournia, M Nazemipour, AI Naimi, GS Collins, MJ Campbell
International Journal of Epidemiology 50 (1), 346-351, 2021
Estimating risk ratios and risk differences using regression
AI Naimi, BW Whitcomb
American journal of epidemiology 189 (6), 508-510, 2020
Mediation analysis for health disparities research
AI Naimi, ME Schnitzer, EEM Moodie, LM Bodnar
American journal of epidemiology 184 (4), 315-324, 2016
Extreme heat and risk of early delivery among preterm and term pregnancies
N Auger, AI Naimi, A Smargiassi, E Lo, T Kosatsky
Epidemiology 25 (3), 344-350, 2014
Big data: a revolution that will transform how we live, work, and think
AI Naimi, DJ Westreich
American Journal of Epidemiology 179 (9), 1143-1144, 2014
Mediation misgivings: ambiguous clinical and public health interpretations of natural direct and indirect effects
AI Naimi, JS Kaufman, RF MacLehose
International journal of epidemiology 43 (5), 1656-1661, 2014
Secular trends in preeclampsia incidence and outcomes in a large Canada database: a longitudinal study over 24 years
N Auger, ZC Luo, AM Nuyt, JS Kaufman, AI Naimi, RW Platt, WD Fraser
Canadian Journal of Cardiology 32 (8), 987. e15-987. e23, 2016
Analysis of occupational asbestos exposure and lung cancer mortality using the g formula
SR Cole, DB Richardson, H Chu, AI Naimi
American journal of epidemiology 177 (9), 989-996, 2013
Altered mitochondrial regulation in quadriceps muscles of patients with COPD
AI Naimi, J Bourbeau, H Perrault, J Baril, C Wright‐Paradis, A Rossi, ...
Clinical physiology and functional imaging 31 (2), 124-131, 2011
Human chorionic gonadotropin partially mediates phthalate association with male and female anogenital distance
JJ Adibi, MK Lee, AI Naimi, E Barrett, RH Nguyen, S Sathyanarayana, ...
The Journal of Clinical Endocrinology & Metabolism 100 (9), E1216-E1224, 2015
Challenges in obtaining valid causal effect estimates with machine learning algorithms
AI Naimi, AE Mishler, EH Kennedy
American Journal of Epidemiology 192 (9), 1536-1544, 2023
Causal inference in occupational epidemiology: accounting for the healthy worker effect by using structural nested models
AI Naimi, DB Richardson, SR Cole
American journal of epidemiology 178 (12), 1681-1686, 2013
Machine learning as a strategy to account for dietary synergy: an illustration based on dietary intake and adverse pregnancy outcomes
LM Bodnar, AR Cartus, SI Kirkpatrick, KP Himes, EH Kennedy, ...
The American journal of clinical nutrition 111 (6), 1235-1243, 2020
Teaching yourself about structural racism will improve your machine learning
WR Robinson, A Renson, AI Naimi
Biostatistics 21 (2), 339-344, 2020
Machine learning for fetal growth prediction
AI Naimi, RW Platt, JC Larkin
Epidemiology 29 (2), 290-298, 2018
Estimating the effect of cumulative occupational asbestos exposure on time to lung cancer mortality: using structural nested failure-time models to account for healthy-worker …
AI Naimi, SR Cole, MG Hudgens, DB Richardson
Epidemiology 25 (2), 246-254, 2014
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