Mandy Mejia

Mandy Mejia

Assistant Professor, Statistics

Education

  • Ph.D., Biostatistics, Johns Hopkins School of Public Health

Research interests

I am interested in the development of statistical methods for the analysis of brain imaging data. My recent or ongoing projects include:

High-dimensional outlier detection methods for artifact removal in fMRI data

Empirical Bayes shrinkage estimation of subject-level resting-state functional connectivity

Bayesian spatial modeling in task activation studies using cortical surface fMRI

Empirical Bayesian techniques to account for spatial dependence in fMRI task activation studies

Leveraging big fMRI datasets for estimation of subject-level and group-level resting-state networks through “template” independent component analysis (ICA)

Synthesis of quantitative structural MR images (e.g. quantitative T1 maps, DTI, MTR) using conventional sequences (e.g. T1-weighted and FLAIR)

Representative publications

Open data on industry payments to healthcare providers reveal potential hidden costs to the public (2019)
Jorge Mejia, Amanda Mejia, Franco Pestilli
Nature communications, 10 (1), 1-8

Template Independent Component Analysis: Targeted and Reliable Estimation of Subject-level Brain Networks using Big Data Population Priors (2019)
Amanda F Mejia, Mary Beth Nebel, Yikai Wang, Brian S Caffo, Ying Guo
arXiv preprint arXiv:1906.07294, 1-58

A Bayesian general linear modeling approach to cortical surface fMRI data analysis (2019)
Amanda F Mejia, Yu Yue, David Bolin, Finn Lindgren, Martin A Lindquist
Journal of the American Statistical Association, 1-26

Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage (2018)
Amanda F Mejia, Mary Beth Nebel, Anita D Barber, Ann S Choe, James J Pekar, Brian S Caffo, Martin A Lindquist
NeuroImage, 172 478-491

Big Data and Neuroimaging (2017)
Yenny Webb-Vargas, Shaojie Chen, Aaron Fisher, Amanda Mejia, Yuting Xu, Ciprian Crainiceanu, Brian Caffo, Martin A Lindquist
Statistics in biosciences, 9 (2), 543-558

PCA leverage: outlier detection for high-dimensional functional magnetic resonance imaging data (2017)
Amanda F Mejia, Mary Beth Nebel, Ani Eloyan, Brian Caffo, Martin A Lindquist
Biostatistics, 18 (3), 521-536

Independent association of severity of muscle weakness with disability as measured by the health assessment questionnaire disability index in scleroderma (2016)
Julie J Paik, Fredrick M Wigley, Amanda F Mejia, Laura K Hummers
Arthritis care & research, 68 (11), 1695-1703

Effects of Scan Length and Shrinkage on Reliability of Resting-State Functional Connectivity in the Human Connectome Project (2016)
Amanda F Mejia, Mary Beth Nebel, Anita D Barber, Ann S Choe, Martin A Lindquist
arXiv preprint arXiv:1606.06284, 1-26

Statistical estimation of T1 relaxation times using conventional magnetic resonance imaging (2016)
Amanda F Mejia, Elizabeth M Sweeney, Blake Dewey, Govind Nair, Pascal Sati, Colin Shea, Daniel S Reich, Russell T Shinohara
NeuroImage, 133 176-188

Statistical Methods for Functional Magnetic Resonance Imaging Data (2016)
Amanda Mejia
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Statistical estimation of white matter microstructure from conventional MRI (2016)
Leah H Suttner, Amanda Mejia, Blake Dewey, Pascal Sati, Daniel S Reich, Russell T Shinohara
NeuroImage: Clinical, 12 (), 615-623

A lag functional linear model for prediction of magnetization transfer ratio in multiple sclerosis lesions (2016)
Gina-Maria Pomann, Ana-Maria Staicu, Edgar J Lobaton, Amanda F Mejia, Blake E Dewey, Daniel S Reich, Elizabeth M Sweeney, Russell T Shinohara
The Annals of Applied Statistics, 10 (4), 2325-2348

Improving reliability of subject-level resting-state fMRI parcellation with shrinkage estimators (2015)
Amanda F Mejia, Mary Beth Nebel, Haochang Shou, Ciprian M Crainiceanu, James J Pekar, Stewart Mostofsky, Brian Caffo, Martin A Lindquist
NeuroImage, 112 (), 14-29

Evidence for specificity of motor impairments in catching and balance in children with autism (2015)
Katarina Ament, Amanda Mejia, Rebecca Buhlman, Shannon Erklin, Brian Caffo, Stewart Mostofsky, Ericka Wodka
Journal of autism and developmental disorders, 45 (3), 742-751

Left‐hemispheric microstructural abnormalities in children with high‐functioning autism spectrum disorder (2015)
Daniel Peterson, Rajneesh Mahajan, Deana Crocetti, Amanda Mejia, Stewart Mostofsky
Autism Research , 8 (1), 61-72