Statistics Ph.D. Student

Harvard University

I'm a Graduate Student in Statistics at Harvard University.

In recent years I've become interested in understanding the principles that lead to successful model building and developing tools to guide practitioners to this end. One instance being tools for detecting practically unidentifiable parameters in Bayesian Models. These methodological developments have always been guided by collaborations with wonderful researchers in public health, political science and, recently, astrophysics. You can find a list of past and current projects below.

In my past I studied Mathematics and Statistics at the University of California, Davis, then more Statistics at University of California, Berkeley. After I had had enough of studying, I spent some time consulting in the San Francisco bay area before taking a position as a Statistician in the Biostatistics unit of the UC Irvine Institute for Clinical and Translational Sciences. I've always believed in developing statistical methodology using the bench-to-bedside approach and my time at UC Irvine helped me solidify this in practice.

I've had the pleasure of assisting in teaching several semester-long courses, here are some.

- Foundations of Quantitative Analysis and People Analytics for the Harvard Business Analytics Program, Harvard Business School in Fall 2018
- Statistical Inference I - Statistics 211, Harvard University in Fall 2017 with Lucas Janson
- Data Science - Computer Science 109B, Harvard University in Spring 2017 with Mark Glickman and others
- Statistical Inference I - Statistics 211, Harvard University in Fall 2016 with Tirthankar Dasgupta
- Introduction to Data Science - Biostatistics 260, Harvard University in Spring 2016 with Rafael Irizarry and Stephanie Hicks
- Data Science - Computer Science 109, Harvard University in Fall 2015 with Joe Blitzstein and others
- Introductory Probability and Statistics for Business - Statistics 21, U.C. Berkeley in Spring 2012

I've also helped create material for these courses. Here are some examples

- Lesson on Cross-validation, Linear and Logistic Regression for Introductory Data Science in Fall 2015 with video lecture
- Lesson on Decision Trees and Random Forests for Introductory Data Science in Fall 2015 with video lecture
- Discussing Final Projects and discussing an example for Introductory Data Science in Fall 2015 with video lecture

- Ph.D. Statistics, Harvard University [
**In Progress**] - M.A. Statistics, University of California, Berkeley [
**2012**] - B.S. Mathematics and Statistics, University of California, Davis [
**2009**]

Statistical Methodology:

- Campos LF, Glickman ME, Hunter KB (2019) Measuring Effects of Medication Adherence on Time-Varying Health Outcomes using Bayesian Dynamic Linear Models.
**In Submission**. - Campos LF, Miratrix LW (2019+) Bayesian Model-Assisted Estimation for Functional Data in Survey Sampling.
**Winner of the 2018 ASA Student Paper Competition for SSS/GSS/SRMS** - Campos LF, Jones DE, Kashyap V, Siemiginowska A, Meng XL, van Dyk DA (2019+) Disentangling Overlapping X-ray Sources II: Using Spatial, Spectral, and Temporal Information.
- Campos LF, Yuan LH, Feller A, Miratrix LW (2019+). Worth Modeling? Model Adjustment for Causal Effects with Zero-Inflated Outcomes.

Healthcare Provider Profiling:

- Chen Y, Rhee CM, Şentürk D, Campos LF, Li Y, Kalantar-Zadeh K, and Nguyen DV (2018) Association of U.S. Dialysis Facility Staffing with Profiling of Hospital-Wide 30-Day Unplanned Readmission. Submitted.

*2018*

- Şentürk D, Chen Y, Estes JP,Campos LF, Rhee CM, Kalantar-Zadeh K and Nguyen DV (2018)Impact of Case-Mix Measurement Error on Estimation and Inference in Profiling of Health CareProviders., Communications in Statistics - Simulation and Computation, doi: 10.1080/03610918.2018.1515360
- Miratrix LW, Sekhon JS, Theodoridis AG, Campos LF (2018) Worth Weighting? How to Think About and Use Sample Weights in Survey Experiments. Political Analysis Volume 26, Issue 3, pp. 275-291. doi:10.1017/pan.2018.1.

*2017*

- Campos LF, Şentürk D, Chen Y, Nguyen DV (2017) Bias and estimation under misspecification of the risk period in self-controlled case series studies. Stat, 6: 4–13 doi:10.1002/sta4.166.

*2015*

*Book Review*- Sudipto Banerjee, Bradley P. Carlin, and Alan E. Gelfand,*Hierarchical Modeling and Analysis for Spatial Data*(2nd ed.) Branson ZJ, Campos LF and Miratrix LW. Journal of the American Statistical Association, 110(512), 1818–1824- Covarrubias N, Bhatia S, Yee S, Campos LF, Nguyen DV, Fish D, Chang E (2015) The relationship between taekwondo training habits and injury: A survey of a collegiate taekwondo population. Open Access Journal of Sports Medicine, 6, 121-127. PMID: 25960680

*2012*

- Hamlin A, Sukharev D, Campos L, Mu Y, Tassone F, Hessl D, Nguyen DV, Loesch D, Hagerman RJ (2012) Hypertension in FMR1 premutation males with and without fragile X-associated tremor/ataxia syndrome (FXTAS). American Journal of Medical Genetics, 158A, 1304-1309. PMID: 22528549

*2011*

- Narcisa V, Aguilar D, Nguyen DV,Campos LF, Brodovsky J, White S, Adams P, Tassone F,Hagerman PJ and Hagerman RJ (2011) A quantitative assessment of tremor and ataxia in female FMR1 premutation carriers using CATSYS. Current Gerontology and Geriatrics Research, vol 2011, Article 484713, 1-7. PMID: 23008705

*2010*

- Schwartzkroin PA, Wenzel HJ, Lyeth BG, Poon CC, DeLance A, Van KC, Campos LF and Nguyen DV (2010) Ketogenic diet modulation of seizure sensitivity and cell loss following fluid percussion injury. Epilepsy Research, 92, 74-84. PMID: 20863664
- Chonchaiya W, Tassone F, Ashwood P, Hessl D, Schneider A, Campos LF, Nguyen DV and Hagerman RJ (2010) Autoimmune disease in mothers with the FMR1 premutation is associated with seizures in their children with fragile X syndrome. Human Genetics, 128, 539-548. PMID: 2080927
- Garcia-Arocena D, Yang JE, Brouwer J, Tassone F, Iwahashi C, Berry-Kravis EM, Goetz CG, Sumis AM, Zhou L, Nguyen DV, Campos LF, Ludwig A, Raske C, Leehey M, Greco C, Willemsen R, Hagerman RJ, Hagerman PJ (2010) Fibroblast phenotype in male carriers of the FMR1 premutation alleles. Human Molecular Genetics, 15, 299-312. PMID: 19864489

- Modeling time-varying health outcomes and medication adherence, VA Medical Center, Bedford, MA, 12/5/2018
- Disentangling astronomical sources with spatial, spectral and temporal X-ray data with an application to binary Young Stellar Objects, Joint Research Conference 2018, Santa Fe, NM, 6/11-14/2018
- Bayesian Model-Assisted Estimation for Functional Data in Survey Sampling, Joint Statistical Meetings 2018, Vancouver, B.C., 7/28-8/2/2018
- Statistical Problems in Astrophysics, SACNAS New England Regional Conference 2018, Worcester, MA, 4/21/2018
- Estimating Causal Effects with Zero-Inflated Outcomes, The Society for Research in Educational Effectiveness, Spring Meeting 2018, Washington, D.C, 2/28/2018
- Disentangling astronomical sources with spatial, spectral and temporal X-ray data, RISE-ASTROSTAT Collaboration Meeting, Heraklion, Crete, Greece. 6/26/2017
- Bayesian Modeling of Functional Data in Survey Sampling, Harvard University, 4/19/2016
- Estimation under misspecification of the risk period in the self-controlled case series method with application to vaccine safety studies (continued work) - WNAR/IMS, University of Hawaii at Manoa, 6/17/2014
- A solution to the misspecification of the optimal risk period in the self-controlled case series method with application to vaccine safety - WNAR/IMS, UCLA, 6/16/2013