Nicole Lazar

Professor of Statistics

Nicole Lazar

Huck Graduate Students

Huck Affiliations

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Most Recent Publications

FUNCTIONAL FACTOR MODELING OF BRAIN CONNECTIVITY

Kyle Stanley, Nicole Lazar, Matthew Logan Reimherr, 2025, Annals of Applied Statistics on p. 1553-1577

Brainpack: a suite of advanced statistical techniques for multi-subject and multi-group fMRI data analysis

Arunava Samaddar, Brooke S. Jackson, Nicole A. Lazar, Jennifer E. McDowell, Cheolwoo Park, 2025, Journal of the Korean Statistical Society

IMS awards: Why your nomination is important

Peter Buhlmann, Nicole Lazar, 2023, IMS Bulletin

Functional neuroimaging in the era of Big Data and Open Science: A modern overview

Nicole A. Lazar, 2023, Wiley Interdisciplinary Reviews: Computational Statistics

Hypothesis testing for shapes using vectorized persistence diagrams

Chul Moon, Nicole A. Lazar, 2023, Journal of the Royal Statistical Society. Series C: Applied Statistics on p. 628-648

Best practices for selecting samples, analyzing data, and publishing results in isotope archaeology

Petra Vaiglova, Nicole A. Lazar, Elizabeth A. Stroud, Emma Loftus, Cheryl A. Makarewicz, 2023, Quaternary International on p. 86-100

Perils and opportunities of ChatGPT: A high school perspective

Nicole Lazar, James Byrns, Diane Crowe, Megan McGinty, Angela Abraham, Mike Guo, Megan Mann, Prithvi Narayanan, Lydia Roberts, Benjamin Sidore, Maxwell Wager, 2023, Harvard Data Science Review

Radical and not-so-radical principles and practices: Discussion of Meng

Ronald Wasserstein, Allen Schirm, Nicole Lazar, 2023, The New England Journal of Statistics and Data Science

How to write about alternatives to classical hypothesis testing outside of the statistical literature: Approximate Bayesian model selection applied to a biomechanics study

Christopher T. Franck, Michael L. Madigan, Nicole A. Lazar, 2022, Stat

Evaluation of the Use of P Values in Neurosurgical Literature: from Statistical Significance to Clinical Irrelevance

Iris S.C. Verploegh, Nicole A. Lazar, Ronald H.M.A. Bartels, Victor Volovici, 2022, World Neurosurgery on p. 280-283.e3

Most-Cited Papers

The ASA's Statement on p-Values: Context, Process, and Purpose

Ronald L. Wasserstein, Nicole A. Lazar, 2016, American Statistician on p. 129-133

Moving to a World Beyond “p < 0.05”

Ronald L. Wasserstein, Allen L. Schirm, Nicole A. Lazar, 2019, American Statistician on p. 1-19

A Meta-Analysis of fMRI Activation Differences during Episodic Memory in Alzheimer's Disease and Mild Cognitive Impairment

Douglas P. Terry, Dean Sabatinelli, A. Nicolas Puente, Nicole A. Lazar, L. Stephen Miller, 2015, Journal of Neuroimaging on p. 849-860

Bayesian empirical likelihood for ridge and lasso regressions

Adel Bedoui, Nicole A. Lazar, 2020, Computational Statistics and Data Analysis

Best practices for selecting samples, analyzing data, and publishing results in isotope archaeology

Petra Vaiglova, Nicole A. Lazar, Elizabeth A. Stroud, Emma Loftus, Cheryl A. Makarewicz, 2023, Quaternary International on p. 86-100

Volubility of the human infant: Effects of parental interaction (or lack of it)

Suneeti Nathani Iyer, Hailey Denson, Nicole Lazar, D. Kimbrough Oller, 2016, Clinical Linguistics and Phonetics on p. 470-488

Nonparametric variogram modeling with hole effect structure in analyzing the spatial characteristics of fMRI data

Jun Ye, Nicole A. Lazar, Yehua Li, 2015, Journal of Neuroscience Methods on p. 101-115

Some properties of generalized fused lasso and its applications to high dimensional data

Woncheol Jang, Johan Lim, Nicole A. Lazar, Ji Meng Loh, Donghyeon Yu, 2015, Journal of the Korean Statistical Society on p. 352-365

A review of empirical likelihood

Nicole A. Lazar, 2021, Annual Review of Statistics and Its Application on p. 329-344

Persistence Terrace for Topological Inference of Point Cloud Data

Chul Moon, Noah Giansiracusa, Nicole A. Lazar, 2018, Journal of Computational and Graphical Statistics on p. 576-586