Jeff Goldsmith

Published

J. Goldsmith, B. S. Caffo, C. M. Crainiceanu, D. Reich, Y. Du, C. W. Hendrix (2011). Nonlinear Tube-Fitting for the Analysis of Anatomical and Functional Structures. Annals of Applied Statistics, 5 337-363. [PubMed]

J. Goldsmith, J. Bobb, C. M. Crainiceanu, B. S. Caffo, D. S. Reich (2011). Penalized Functional Regression. Journal of Computational and Graphical Statistics, 20 830-851. [pdf | Simulation code | R function]

J. Goldsmith, C. M. Crainiceanu, B. S. Caffo, D. S. Reich (Accepted). Longitudinal Penalized Functional Regression for Cognitive Outcomes on Neuronal Tract Measurements. Journal of the Royal Statistical Society: Series C. [pdf | Simulation code | R function]

J. Goldsmith, C. M. Crainiceanu, B. S. Caffo, D. S. Reich (2011). Penalized Functional Regression Analysis of White-Matter Tract Profiles in Multiple Sclerosis. NeuroImage, 57 431-439. [PubMed]

J. Goldsmith, M. P. Wand, and C. M. Crainiceanu (2011). Functional Regression via Variational Bayes. Electronic Journal of Statistics, 5 572-602. [PubMed | code]

T. Shinohara, J. Goldsmith, F. Mateen, D. S. Reich, C. M. Crainiceanu (Accepted). Predicting Breakdown of the Blood-Brain Barrier in Multiple Sclerosis Without Contrast Agents. American Journal of Neuroradiology.

N. Louissant, S. Nimmagadda, E. Fuchs, R. Bakshi, Y. Cao, L. Lee, J. Goldsmith, B. S. Caffo, Y. Du, K. King, F. Menendez, M. Torbenson, R. Wahl, C. W. Hendrix (Accepted). Distribution of Cell-free and Cell-associated HIV Surrogates in the Colon following Simulated Receptive Anal Intercourse. Journal of Acquired Immune Deficiency Syndromes. [PubMed]

C. M. Crainiceanu, J. Goldsmith (2010). Bayesian Functional Data Analysis using WinBUGS. Journal of Statistical Software, 32 1-33. [PubMed]

J. Goldsmith, L. Koss (2009). Dynamical Properties of the Derivative of the Weierstrass Elliptic Function. Involve, 2 267-288. [pdf]

Submitted

J. Goldsmith, L. Huang, C. M. Crainiceanu. Smooth Scalar-on-Image Regression.

J. Goldsmith, S. Greven, C. M. Crainiceanu. Corrected Confidence Bands for Functional Data Using Principal Components. [pdf]

J. Bai, J. Goldsmith, B. S. Caffo, T. Glass, C. M. Crainiceanu. Movelets: A Dictionary of Movement. [pdf]

N. Louissant, S. Nimmagadda, R. Bakshi, Y. Du, K. Macura, K. King, R. Wahl, J. Goldsmith, B. S. Caffo, Y.-J. Cao, J. Anderson, E. Fuchs, C. W. Hendrix. Distribution of Cell-free and Cell-associated HIV Surrogates in the Female Genital Tract following Simulated Vaginal Intercourse.

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I am inspired by current scientific questions to develop general, principled methods for the analysis of challenging data sets. At this time, my research is driven by three main scientific problems: (i) studying the longitudinal changes in brain images of multiple sclerosis subjects and healthy controls and their association with cognitive and motor outcomes; (ii) parameterizing the distribution of multidimensional data with application to HIV microbicide pharmacokinetics; and (iii) predicting activity type from 3-axes accelerometer data for use in observational studies of an aging population. The methodological developments motivated by these studies are modern functional data analysis tools required by new data structures and scientific problems.

Below are a few images stemming from my recent work.

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This is a brain; two major white matter tracts, the corpus callosum and corticospinal tracts, are shown in red and blue respectively.

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When recorded by a single, three axis accelerometer worn at the hip, the activites walking, laying and standing have the following appearance:

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The figure below illustrates the data structure observed for longitudinal studies in which scalar outcomes and functional predictors are obtained at each of several visits.

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Fall 2011

280.345: Biostatistics for Public Health Majors (Undergraduate course), Co-instructor.

Fall 2010 - Spring 2011

140.622-623: Statistical Methods in Public Health, Lead TA.

Fall 2010

140.751: Advanced Methods in Biostatistics.

Fall 2009

140.621-622: Statistical Methods in Public Health, Lead TA.

Fall 2008 - Spring 2009

140.651-654: Intermediate Methods in biostatistics.

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R packages

refund

The following functions are contributions to the refund package available on CRAN (these can also be downloaded and installed directly from this website):

• pfr - this function implements the methods developed in "Penalized Functional Regression".
• lpfr - this function implements the methods developed in "Longitudinal Penalized Functional Regression for Cognitive Outcomes on Neuronal Tract Measurements".

Importantly, these functions allow multiple functional predictors, missingness in the functional predictors, and return coefficient functions with confidence bounds.

Other code

• Supplementary material to "Functional Regression via Variational Bayes" - includes illustrative examples for the use of variational Bayes in functional regession in both cross-sectional and longitudinal settings. Also includes WinBUGS code for the comparison of variational Bayes to MCMC.
• Supplementary material to "Penalized Functional Regression" - includes code used in all simulations as well as straightforward examples.

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CV

A pdf of my CV can be found here.

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