Dr. Ram Shanmugam

School of Health Administration

Texas State University, USA.

Professor

E-mail: rs25@txstate.edu

Qualifications

1979 Ph.D., Applied Statistics, Temple University, USA

1874 M.S., Operations Research, Rensselaer Polytechnic, USA

1965 B.Sc., Statistics and Numerical Mathematics, Loyola College, India

Research Fields

Healthcare data analysis

Decision Making, Econometrics

Operations research

Healthcare & Hospital Management Issues

Insurance Economics

Publications (selected)

1. Shanmugam, R. (2015) Never, once, and repeated illness: a geometric view for insights and interpretations, International Journal of Research in Medical Sciences, 3(6), 1336-1341.
2. Shanmugam, R. (2015) Refined randomized response model for suspicious answers: Illicit drug users in U.S.A. are illustrated, International Journal of Ecological Economics & Statistics, 36, 15-27.
3. Shanmugam, R. (2015) Entropy nucleus and use in waste disposal policies, International Journal on Information Theory (IJIT), 4 (2), 1-12.
4. Zhang, Y., Singh, J. and Shanmugam, R. (2014). Modeling to capture covariate effect, accepted to appear in Communications in Statistics, page numbers are pending.
5. Shanmugam, R. (2015) Whether Gaussian nucleus entropy helps? Case in point is prediction of number of cesarean births, American Journal of Biostatistics, (page numbers are pending).
6. Shanmugam, R. (2015) Geometric view of odds tilted binomial model and its use to analyze asthma incidences data among monozygotic versus dizygotic twins, International Journal of Medical Science Research and Practice, 1 (1), 1-5.
7. Shanmugam, R. (2014) Health broken woven Poisson spheres to manage deadly Ebola incidences, American Journal of Infectious Diseases, 10, 143-154.
8. Shanmugam, R. (2014). “Bivariate Distribution” for infrastructures among operative, natural, and no menopauses, American Journal of Biostatistics, 4, 34-44.
9. Shanmugam, R. (2014). How do queuing concepts and tools help to effectively manage hospitals when the patients are impatient? A demonstration, International Journal of Research in Medical Sciences, 2, 1076-1084.
10. Shanmugam, R. (2014). A bivariate probability model to identify “honesty” versus “cheating” in economic surveys: Xenophobia is illustrated. Am. J. Econ. Bus. Admin., 6: 42-48.
11. Shanmugam, R. (2014). C(∝) method to check daunting over/under variances to understand times to aftershocks since a major earthquake, Computer, Electronics, Electrical, and Communication, 59, 190-193.
12. Shanmugam, R. (2014). Data guided public healthcare decision making, Volume II, Category: Medicare and Healthcare Administration, Encyclopedia of Business Analytics and Optimization, edited by John Wang. pp. 30-43.
13. Shanmugam, R. (2014). Probing non-adherence to prescribed medicines? A bivariate distribution with information nucleus clarifies, American Medical Journal, 5(2), 56-62.
14. Shanmugam, R. (2014). Data envelopment analysis for operational efficiency, Volume II, Category: Data Envelopment Analysis, Encyclopedia of Business Analytics and Optimization, edited by John Wang. pp. 18-28. Singh, H. P.
15. Shanmugam, R., Singh, S., and Kim, J. M. (2014). Estimation of median in the presence of three known quartiles of an auxilary variable, Communication for Statistical Applications and Methods, 21, 1-24.
16. Shanmugam, R. (2014). Stochastic frontier analysis and cancer survivability, Volume V, Category: Stochastic Models, Encyclopedia of Business Analytics and Optimization, edited by John Wang. pp. 18-26.
17. Shanmugam, R. (2014). Over/under dispersion sometimes necessitates modifying, International Journal of Statistics and Poisson model with illustration of tetanus cases and deaths after tsunami, International Journal of Ecological Economics & Statistics, 34(3), 37-42.
18. Shanmugam, R. (2014). Revelation of shrunken or stretched binomial dispersion and public perception of situations, which might spread AIDS or HIV, International Journal of Research in Medical Sciences, 2(2), .462-467.
19. Shanmugam, R. (2014). Tweaked binomial distribution to capture the impact of drilling to cure bioterror victims in hospitals, International Journal of Statistics and Economics, 13(1), 40-45.
20. Shanmugam, R. (2014). An assessment of nurses’ sufficient immunity when treating infectious patients using bumped-up binomial model, International Journal of Research in Medical Sciences, 2(1), 132-138.

Profile Details：

http://www.health.txstate.edu/ha/fac-staff/fac/r-shanmugam.html

Last Updated:2015-07-06