Recent Publications

Jeremy Coyle, Nima Hejazi, Ivana Malenica, Rachael Phillips, Benjamin Arnold, Andrew Mertens, Jade Benjamin-Chung, Weixin Cai, Sonali Dayal, John Colford Jr., Alan Hubbard, Mark van der Laan (2020). Targeted Learning: robust statistics for reproducible research.

Ashkan Ertefaie, Nima Hejazi, Mark van der Laan (2020). Nonparametric inverse probability weighted estimators based on the highly adaptive lasso.

Preprint Project

Nima Hejazi, Mark van der Laan, Holly Janes, Peter Gilbert, David Benkeser (2020). Efficient nonparametric inference on the effects of stochastic interventions under two-phase sampling, with applications to vaccine efficacy trials.

Preprint Code Project Slides

Philippe Boileau, Nima Hejazi, Sandrine Dudoit (2020). Exploring high-dimensional biological data with sparse contrastive principal component analysis. In Bioinformatics.

Preprint PDF Code Project DOI

Philippe Boileau, Nima Hejazi, Sandrine Dudoit (2020). scPCA: A toolbox for sparse contrastive principal component analysis in R. In Journal of Open Source Software.

PDF Code Project Source Document DOI

Iván Díaz, Nima Hejazi (2020). Causal mediation analysis for stochastic interventions. In Journal of the Royal Statistical Society, Series B (Statistical Methodology).

Preprint PDF Code Project Project DOI

Iván Díaz, Nima Hejazi, Kara Rudolph, Mark van der Laan (2019). Non-parametric efficient causal mediation with intermediate confounders.

Preprint Code Project

Nima Hejazi, Mark van der Laan, Alan Hubbard (2019). A generalization of moderated statistics to data adaptive semiparametric estimation in high-dimensional biology.

Preprint Code Slides

Amin Sobh, Alex Loguinov, Gulce Naz Yazici, Rola Zeidan, Abderrahmane Tagmount, Nima Hejazi, Alan Hubbard, Luoping Zhang, Chris Vulpe (2019). Functional profiling identifies determinants of arsenic trioxide cellular toxicity. In Toxicological Sciences.

PDF Project DOI

Weixin Cai, Alan Hubbard, Nima Hejazi (2018). adaptest: Data-adaptive statistics for high-dimensional testing in R. In Journal of Open Source Software.

PDF Code Source Document DOI

Nima Hejazi, Rachael Phillips, Alan Hubbard, Mark van der Laan (2018). methyvim: Targeted, robust, and model-free differential methylation analysis. In F1000Research.

PDF Code Slides Source Document

Jeremy Coyle, Nima Hejazi (2018). origami: A generalized framework for cross-validation in R. In Journal of Open Source Software.

PDF Code Source Document DOI

Nima Hejazi, Weixin Cai, Alan Hubbard (2017). biotmle: Targeted Learning for biomarker discovery. In Journal of Open Source Software.

PDF Code Source Document DOI

Nima Hejazi (2017). Generalized application of empirical Bayes statistics to asymptotically linear parameters. Master’s thesis, Graduate Division, University of California, Berkeley.

PDF Code Slides

Weixin Cai, Nima Hejazi, Alan Hubbard (2017). Data-adaptive statistics for multiple hypothesis testing in high-dimensional settings.