Jeff Goldsmith
Jeff Goldsmith
Associate Professor, Department of Biostatistics, Columbia University
Verified email at - Homepage
Cited by
Cited by
Fitbit®: An accurate and reliable device for wireless physical activity tracking
KM Diaz, DJ Krupka, MJ Chang, J Peacock, Y Ma, J Goldsmith, ...
International journal of cardiology 185, 138-140, 2015
Penalized functional regression
J Goldsmith, J Bobb, CM Crainiceanu, B Caffo, D Reich
Journal of Computational and Graphical Statistics 20 (4), 830-851, 2010
Statistical normalization techniques for magnetic resonance imaging
RT Shinohara, EM Sweeney, J Goldsmith, N Shiee, FJ Mateen, ...
NeuroImage: Clinical 6, 9-19, 2014
Multicenter study of planar technetium 99m pyrophosphate cardiac imaging: predicting survival for patients with ATTR cardiac amyloidosis
A Castano, M Haq, DL Narotsky, J Goldsmith, RL Weinberg, ...
JAMA cardiology 1 (8), 880-889, 2016
Assessing the “physical cliff”: detailed quantification of age-related differences in daily patterns of physical activity
JA Schrack, V Zipunnikov, J Goldsmith, J Bai, EM Simonsick, ...
Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences …, 2014
Corrected Confidence Bands for Functional Data Using Principal Components
J Goldsmith, S Greven, CM Crainiceanu
Biometrics 69 (1), 41-51, 2013
Longitudinal penalized functional regression for cognitive outcomes on neuronal tract measurements
J Goldsmith, CM Crainiceanu, B Caffo, D Reich
Journal of the Royal Statistical Society: Series C (Applied Statistics) 61 …, 2012
Refund: Regression with functional data
J Goldsmith, F Scheipl, L Huang, J Wrobel, J Gellar, J Harezlak, ...
R package version 0.1-16 572, 2016
Prevalence and prognostic significance of low QRS voltage among the three main types of cardiac amyloidosis
NB Cyrille, J Goldsmith, J Alvarez, MS Maurer
The American journal of cardiology 114 (7), 1089-1093, 2014
Methods for scalar‐on‐function regression
PT Reiss, J Goldsmith, HL Shang, RT Ogden
International Statistical Review 85 (2), 228-249, 2017
refund: Regression with functional data
C Crainiceanu, P Reiss, J Goldsmith, L Huang, L Huo, F Scheipl, ...
R package version 0.1-6, 2012
Generalized Multilevel Functional-on-Scalar Regression and Principal Component Analysis
J Goldsmith, V Zipunnikov, J Schrack
Bayesian functional data analysis using WinBUGS
CM Crainiceanu, J Goldsmith
Journal of Statistical Software 32 (11), 1-25, 2009
Smooth Scalar-on-Image Regression via Spatial Bayesian Variable Selection
J Goldsmith, L Huang, CM Crainiceanu
Journal of Computational and Graphical Statistics 23, 46-64, 2014
An introduction with medical applications to functional data analysis
H Sorensen, J Goldsmith, LM Sangalli
Statistics in Medicine 32 (5222-5240), 2013
To excise or not: impact of MelaFind on German dermatologists’ decisions to biopsy atypical lesions
A Hauschild, SC Chen, M Weichenthal, A Blum, HC King, J Goldsmith, ...
JDDG: Journal der Deutschen Dermatologischen Gesellschaft 12 (7), 606-614, 2014
A short and distinct time window for recovery of arm motor control early after stroke revealed with a global measure of trajectory kinematics
JC Cortes, J Goldsmith, MD Harran, J Xu, N Kim, HM Schambra, AR Luft, ...
Neurorehabilitation and neural repair 31 (6), 552-560, 2017
Longitudinal scalar-on-functions regression with application to tractography data
J Gertheiss, J Goldsmith, C Crainiceanu, S Greven
Biostatistics 14 (3), 447-461, 2013
Penalized functional regression analysis of white-matter tract profiles in multiple sclerosis
J Goldsmith, CM Crainiceanu, BS Caffo, DS Reich
NeuroImage 57 (2), 431-439, 2011
Robotic therapy for chronic stroke: general recovery of impairment or improved task-specific skill?
T Kitago, J Goldsmith, M Harran, L Kane, J Berard, S Huang, SL Ryan, ...
Journal of neurophysiology 114 (3), 1885-1894, 2015
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