Yungtai Lo

Yungtai Lo, Ph.D.

Email

Phone

Location

  • Albert Einstein College of Medicine Jack and Pearl Resnick Campus 1300 Morris Park Avenue Block 311 Bronx, NY 10461


Research Profiles

Professional Interests

Dr. Lo collaborates with investigators in Departments of Microbiology and Immunology, Medicine, Nephrology, Pathology, and Orthopedics on the design and analysis of clinical trials and epidemiologic studies.  His research interests focus on developing test procedures to determine the number of latent groups in a heterogeneous population and to determine whether mixture distributions are homoscedastic or heteroscedastic, examining bias from misspecification of component variances in mixture models, developing methods for correcting outcome misclassification and  disease progression process, developing methods for modeling semi-continuous data, and applications of mixture models for  estimating disease prevalence and predicting disease likelihood in the absence of gold standard.

Selected Publications

1. Lo Y, Mendell NR, Rubin DB. Testing the number of components in a normal mixture. Biometrika 2001; 88:767-778.

2. Lo Y, Matthysse S, Rubin DB, Holzman PS. Permutation tests for detecting the presence of mixture in task performance within groups. Statistics in Medicine 2002; 21:1937-1953.

3. Coleman MJ, Cook S, Matthysse S, Barnard J,  Lo Y, Levy DL, Rubin DB, Holzman PS. Spatial and object working memory impairment in schizophrenia patients: A Bayesian item-response theory analysis. Journal of Abnormal Psychology 2002; 111:425-435.

4. Howard AA, Arnsten JH, Lo Y, Vlahov D, Rich JD, Schuman P, Stone VE, Smith DK, Schoenbaum EE. A prospective study of adherence and viral load in a large multi-center cohort of HIV-infected women. AIDS 2002; 16:2175-2182.

5. Lo Y. Likelihood ratio tests of the number of components in a normal mixture with unequal variances. Statistics and Probability Letters 2005; 71:225-235.

6. Klein RS, Lo Y, Santoro N, Dobs AS. Androgen levels in older men who have or who are at risk of acquiring HIV infection. Clinical Infectious Diseases 2005; 41:1794-803.

7. Schoenbaum EE, Hartel D, Lo Y, Howard AA, Floris-Moore M, Arnsten JH, Santoro N. HIV infection, drug use and onset of natural menopause. Clinical Infectious Diseases 2006; 41:1517-24.

8. Howard AA, Lo Y, Floris-Moore M, Klein RS, Fleischer N, Schoenbaum EE. Hepatitis C virus infection is associated with insulin resistance among older adults with or at-risk for HIV infection. AIDS 2007; 21:633-641.

9. Lo Y. A likelihood ratio test of a homoscedastic normal mixture against a heteroscedastic normal mixture. Statistics and Computing 2008; 18:233-240.

10. Lo Y. Estimating age-specific prevalence of testosterone deficiency in men using normal mixture models. Journal of Data Sciences 2009; 7:203-217.

11. Floris-Moore M, Fayad ZA, Berman JW, Mani V, Schoenbaum EE, Klein RS, Weinshelbaum KB, Fuster V, Howard AA, Lo Y, Schecter AD. Association of HIV Viral Load with Monocyte Chemoattractant Protein-1 and Atherosclerosis Burden Measured by Magnetic Resonance Imaging. AIDS 2009; 23:941-949.

12. Lo Y. Bias from misspecification of component variances in a normal mixture. Computational Statistics and Data Analysis 2011; 55:2739-2747.

13. Lyles RH, Tang L, Superak HM, King CC, Celentano D, Lo Y, Sobel J. Validation data-based adjustments for outcome misclassification in logistic regression: an illustration. Epidemiology 2011; 22:589-597.

14. Mitchell CE, Hudgens MG, King CC, Cu-Uvin S, Lo Y, Rompalo A, Sobel J, Smith JS. Discrete-time semi-Markov modeling of human papillomavirus persistence. Statistics in Medicine 2011; 2160-70.

15. Soto E, Lo Y, Friedman K, Soto C, Nezhat F, Chuang L, Gretz H. Total laparoscopic hysterectomy versus da Vinci robotic hysterectomy: is using the robot beneficial? Journal of Gynecologic Oncology 2011; 22(4):253-259.

16. Lin CY, Lo Y, Ye KQ. Genotype copy number variations using Gaussian mixture models: theory and algorithms. Statistical Applications in Genetics and Molecular Biology 2012; 11(5):5.

17. Kelller MJ, Malone AM, Carpenter CA, Lo Y, Huang M, Corey L, Willis R, Nguyen C, Kennedy S, Gunawardana M, Guerrero D, Moss J, Baum M, Smith TJ, Herold BC. Safty and pharmacokinetics of acyclovir in women following release from a silicone elastomer vaginal ring. Journal of Antimicrobial Chemotherapy 2012; 67:2005-2012.

18. Keller MJ, Carpenter CA, Lo Y, Einstein MH, Liu C, Fredricks DN, Herold BC. Phase I randomized safety study of twice daily dosing of acidform vaginal gel: candidate antimicrobial contraceptive. PLOS ONE 2012; 7:e46901.

19. Lo Y. Estimating prevalence of low lumbar spine bone mineral density in older men with or at risk for HIV infection using normal mixture models. Journal of Applied Statistics 2012; 39(10):2247-2258.

20. Tang L, Lyles RH, Ye Y, Lo Y, King CC. Extended matrix and inverse matrix methods utilizing internal validation data when both disease and exposure status are misclassified. Epidemiologic Methods 2013; 0:1-18.

21. V. Sarwahi, E.P. Sugaman, T. Amaral, A. Wollowick, Y. Lo, B. Thornhill. Prevalence, distribution and surgical relevance of abnormal pedicles in spine with adolescent idiopathic scoliosis vs. no deformity: a CT-based study. Journal of Bone and Joint Surgery 2014; 96(1):e92.

22. H.S. Suh, Y. Lo, N. Choi, S. Letendre, S. Lee. Evidence of the innate antiviral and neuroprotective properties of progranulin. PLOS ONE 2014; 9(5): e98184.

23. Lo Y. Assessing effects of an intervention on bottle-weaning and reducing daily milk intake from bottles in toddlers using two-part random effects models. Journal of Data Science 2015; 13:1-20.

24. L. Tang, R.H. Lyles, C.C. King, J.W. Hogan, Y. Lo. Regression analysis for differentially misclassified correlated binary outcomes. Journal of the Royal Statistical Society - Series C 2015; 64:433-449.

26. L. Tang, R.H. Lylers, C.C. King, D. Celentano, Y. Lo. Binary regression with differentially misclassified response and exposure variables. Statistics in Medicine 2015; 34(9):1605-20.