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Estimating Risk Ratios and Risk Differences Using Regression

American journal of epidemiology, 2020-06, Vol.189 (6), p.508-510

2020

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Reflection on modern methods: demystifying robust standard errors for epidemiologists

International journal of epidemiology, 2021-03, Vol.50 (1), p.346-351

2021

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Things Don’t Always Go as Expected: The Example of Nondifferential Misclassification of Exposure—Bias and Error

American journal of epidemiology, 2020-05, Vol.189 (5), p.365-368

2020

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Extreme Heat and Risk of Early Delivery Among Preterm and Term Pregnancies

Epidemiology (Cambridge, Mass.), 2014-05, Vol.25 (3), p.344-350

2014

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Does weight mediate the effect of smoking on coronary heart disease? Parametric mediational g-formula analysis

PloS one, 2022-01, Vol.17 (1), p.e0262403-e0262403

2022

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Machine learning as a strategy to account for dietary synergy: an illustration based on dietary intake and adverse pregnancy outcomes

The American journal of clinical nutrition, 2020-06, Vol.111 (6), p.1235-1243

2020

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Effects of Hypothetical Interventions on Ischemic Stroke Using Parametric G-Formula

Stroke (1970), 2019-11, Vol.50 (11), p.3286-3288

2019

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Sexually transmitted infections and risk of hypertensive disorders of pregnancy

Scientific reports, 2022-08, Vol.12 (1), p.13904-13904, Article 13904

2022

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Analysis of ‘sensitive’ periods of fetal and child growth

International journal of epidemiology, 2019-02, Vol.48 (1), p.116-123

2019

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Stacked generalization: an introduction to super learning

European journal of epidemiology, 2018-05, Vol.33 (5), p.459-464

2018

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Use of Sodium-Glucose Cotransporter-2 Inhibitors and Angiotensin Receptor-Neprilysin Inhibitors in Patients With Atrial Fibrillation and Heart Failure From 2021 to 2022: An Analysis of Real-World Data

Journal of the American Heart Association, 2024-03, Vol.13 (6), p.e032783-e032783

2024

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Secular Trends in Preeclampsia Incidence and Outcomes in a Large Canada Database: A Longitudinal Study Over 24 Years

Canadian journal of cardiology, 2016-08, Vol.32 (8), p.987.e15-987.e23

2016

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Challenges in Obtaining Valid Causal Effect Estimates With Machine Learning Algorithms

American journal of epidemiology, 2023-09, Vol.192 (9), p.1536-1544

2023

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An introduction to g methods

International journal of epidemiology, 2017-04, Vol.46 (2), p.756-762

2017

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Defining and Identifying Average Treatment Effects

American journal of epidemiology, 2023-05, Vol.192 (5), p.685-687

2023

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Stochastic Mediation Contrasts in Epidemiologic Research: Interpregnancy Interval and the Educational Disparity in Preterm Delivery

American journal of epidemiology, 2014-08, Vol.180 (4), p.436-445

2014

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Simple Approaches for Dealing With Correlated Data

American journal of epidemiology, 2023-04, Vol.192 (4), p.507-509

2023

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Interaction in Theory and in Practice: Evaluating Combinations of Exposures in Epidemiologic Research

American journal of epidemiology, 2023-06, Vol.192 (6), p.845-848

2023

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Obtaining Actionable Inferences from Epidemiologic Actions

Epidemiology (Cambridge, Mass.), 2019-03, Vol.30 (2), p.243

Naimi, Ashley I

2019

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Invited commentary: Estimating population impact in the presence of competing events

American journal of epidemiology, 2015-04, Vol.181 (8), p.571-574

2015

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Commentary: Integrating Complex Systems Thinking into Epidemiologic Research

Epidemiology (Cambridge, Mass.), 2016-11, Vol.27 (6), p.843-847

Naimi, Ashley I.

2016

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Teaching yourself about structural racism will improve your machine learning

Biostatistics (Oxford, England), 2020-04, Vol.21 (2), p.339-344

2020

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AIPW: An R Package for Augmented Inverse Probability–Weighted Estimation of Average Causal Effects

American journal of epidemiology, 2021-12, Vol.190 (12), p.2690-2699

2021

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On wagging tales about causal inference

International journal of epidemiology, 2017-08, Vol.46 (4), p.1340-1342

Naimi, Ashley I

2017

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A Simulation Study Comparing the Performance of Time-Varying Inverse Probability Weighting and G-Computation in Survival Analysis

American journal of epidemiology, 2023-01, Vol.192 (1), p.102-110

2023

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Estimating Risk Ratios and Risk Differences Using Regression

Reflection on modern methods: demystifying robust standard errors for epidemiologists

Things Don’t Always Go as Expected: The Example of Nondifferential Misclassification of Exposure—Bias and Error

Extreme Heat and Risk of Early Delivery Among Preterm and Term Pregnancies

Does weight mediate the effect of smoking on coronary heart disease? Parametric mediational g-formula analysis

Machine learning as a strategy to account for dietary synergy: an illustration based on dietary intake and adverse pregnancy outcomes

Effects of Hypothetical Interventions on Ischemic Stroke Using Parametric G-Formula

Sexually transmitted infections and risk of hypertensive disorders of pregnancy

Analysis of ‘sensitive’ periods of fetal and child growth

Stacked generalization: an introduction to super learning

Use of Sodium-Glucose Cotransporter-2 Inhibitors and Angiotensin Receptor-Neprilysin Inhibitors in Patients With Atrial Fibrillation and Heart Failure From 2021 to 2022: An Analysis of Real-World Data

Secular Trends in Preeclampsia Incidence and Outcomes in a Large Canada Database: A Longitudinal Study Over 24 Years

Challenges in Obtaining Valid Causal Effect Estimates With Machine Learning Algorithms

An introduction to g methods

Defining and Identifying Average Treatment Effects

Stochastic Mediation Contrasts in Epidemiologic Research: Interpregnancy Interval and the Educational Disparity in Preterm Delivery

Simple Approaches for Dealing With Correlated Data

Interaction in Theory and in Practice: Evaluating Combinations of Exposures in Epidemiologic Research

Obtaining Actionable Inferences from Epidemiologic Actions

Invited commentary: Estimating population impact in the presence of competing events

Commentary: Integrating Complex Systems Thinking into Epidemiologic Research

Teaching yourself about structural racism will improve your machine learning

AIPW: An R Package for Augmented Inverse Probability–Weighted Estimation of Average Causal Effects

On wagging tales about causal inference

A Simulation Study Comparing the Performance of Time-Varying Inverse Probability Weighting and G-Computation in Survival Analysis

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