Nicole Lazar
Professor of Statistics
-
326 Thomas
University Park, PA - nfl5182@psu.edu
- 814-865-1348
Publication Tags
Empirical Likelihood Magnetic Resonance Imaging Regression Brain Invariance Monte Carlo Simulation Generalized Estimating Equations Exact Test Lasso Ridge Regression Persistence Correlation Structure Critical Value Interaction Likelihood Smoothing Metropolis Hastings Estimate Model Misspecification Ridge Functional Neuroimaging Review Infant Swine InferenceMost Recent Papers
A group comparison in fMRI data using a semiparametric model under shape invariance
Arunava Samaddar, Brooke S. Jackson, Christopher J. Helms, Nicole A. Lazar, Jennifer E. McDowell, Cheolwoo Park, 2022, Computational Statistics and Data Analysis
A group comparison in fMRI data using a semiparametric model under shape invariance
A. Samaddar, B. Jackson, C. Helms, Nicole Lazar, J. McDowell, C. Park, 2021, Computational Statistics and Data Analysis
The neuroscience of human connection and leadership
Nicole Lazar, 2021,
An integrative multivariate approach for predicting functional recovery using magnetic resonance imaging parameters in a translational pig ischemic stroke model
Erin Kaiser, J. Poythress, Kelly Scheulin, Brian Jurgielewicz, Nicole Lazar, Cheolwoo Park, Steven Stice, Jeongyoun Ahn, Franklin West, 2021, Neural Regeneration Research on p. 842-850
A review of empirical likelihood
Nicole A. Lazar, 2021, Annual Review of Statistics and Its Application on p. 329-344
Split sample empirical likelihood
Adam Jaeger, Nicole A. Lazar, 2020, Computational Statistics and Data Analysis
Bayesian empirical likelihood for ridge and lasso regressions
Adel Bedoui, Nicole A. Lazar, 2020, Computational Statistics and Data Analysis
Data, data, everywhere...
Nicole Lazar, 2020, Harvard Data Science Review
Moving to a World Beyond “p < 0.05”
Ronald L. Wasserstein, Allen L. Schirm, Nicole A. Lazar, 2019, American Statistician on p. 1-19
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
Most-Cited Papers
The ASA's Statement on p-Values
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
Selection of working correlation structure in generalized estimating equations via empirical likelihood
Jien Chen, Nicole A. Lazar, 2012, Journal of Computational and Graphical Statistics on p. 18-41
Volubility of the human infant
Suneeti Nathani Iyer, Hailey Denson, Nicole Lazar, D. Kimbrough Oller, 2016, Clinical Linguistics and Phonetics on p. 470-488
Incorporating spatial dependence into Bayesian multiple testing of statistical parametric maps in functional neuroimaging
D. Andrew Brown, Nicole A. Lazar, Gauri S. Datta, Woncheol Jang, Jennifer E. McDowell, 2014, NeuroImage on p. 97-112
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
Practice-related changes in neural activation patterns investigated via wavelet-based clustering analysis
Jinae Lee, Cheolwoo Park, Kara A. Dyckman, Nicole A. Lazar, Benjamin P. Austin, Qingyang Li, Jennifer E. Mcdowell, 2013, Human Brain Mapping on p. 2276-2291
Computing critical values of exact tests by incorporating monte carlo simulations combined with statistical tables
Albert Vexler, Young Min Kim, Jihnhee Yu, Nicole A. Lazar, Alan D. Hutson, 2014, Scandinavian Journal of Statistics on p. 1013-1030
Bayesian empirical likelihood for ridge and lasso regressions
Adel Bedoui, Nicole A. Lazar, 2020, Computational Statistics and Data Analysis