Editorial Board Member - JCSB
Chandan SahaAssociate Professor
Department of Biostatistics
School of Medicine
My collaborative research has been in numerous areas including diabetes, pediatric autism and delayed developmental, HIV, hypertension, dermatology, stroke, obesity and fibromyalgia.
- My primary long term research has been in diabetes focusing on preventing diabetes, understanding barriers to insulin initiation and interventions on improving diabetes related clinical outcomes. This major collaboration resulted in several publications, e.g. the long term effect of a community-based lifestyle intervention to prevent type 2 diabetes and reduced 10-year risk of coronary heart disease (Ackerman et. al. Chronic Illness, 2011; Diabetes Care, 2009), barriers to insulin initiation (Diabetes Care, 2010), and use of multimedia technology for improving clinical outcomes through improved communication on cardiovascular disease risk between diabetic patients and physicians (Diabetes Specterm, 2010).
- The second major collaboration I had was in stroke and hypertension. Stroke research includes a wide variety topic, e.g. how children view their abilities, feeding problems in children, cerebral palsy and association with other disability in children with perinatal stroke (Barkat-Masih et. al. Journal of Child Neurology 2011 and 2009, Golomb et. al. Journal of Child Neurology 2008 and 2007). Research in hypertension was on methodologies of identifying hypertension in hemodialysis patients (Agarwal and Saha, Blood pressure monitoring 2007, Agarwal et. al. Kidney international 2006 and 2007), improvement of blood pressure with suppression of ENaC (Saha et. al. Hypertension 2005) and change in blood pressure during pubertal growth (Shankar et. al. The journal of Clinical Endocrinology and Metabolism, 2005).
- Other significant collaborative research includes treatment of HIV related endothelial dysfunction (Gupta et. al. AIDS 2010 and 2008), onset of overweight during childhood and adolescents in relation to race and sex (Saha et. al. The Journal of Clinical Endocrinology and Metabolism 2005) and severe electrocardiographic abnormalities and risk of arrhythmias and sudden death in myotonic dystrophy type I (Groh et. al. New England Journal of Medicine 2008).
Subject dropout is an inevitable problem in longitudinal studies and very often the reason for dropout might be informative. Use of linear mixed effects model in comparing rate of change in outcome and use of last observation carried forward approach (LOCF) in comparing the change in outcome from baseline are very common approaches. In collaboration with Dr. Jones at the University of Iowa, we quantified bias in parameter estimates both for linear mixed effect model and LOCF approach under informative dropout (Saha and Jones, Journal of Royal Statistical Society Series B 2005 and Saha and Jones, Journal of Statistical Planning and Inference 2009). The current follow up research in this area has been quantifying type I and type II error rates in the LOCF approach under informative dropout.
Other Editorial Board Members - JCSB
Department of Computer Science
Department of Molecular & Microbiology
George Mason University
Center for Quantitative Sciences
Abdel-Badeeh M. Salem
Department of Computer and Information sciences
Ain Shams University
Department of Systems & Computational Biology
Department of Biostatistics & Computational Biology
University of Rochester
Department of Computer Science and Engineering
Michigan State University
Department of Computer Science
Virginia Polytechnic Institute and State University
SARATH CHANDRA JANGA
School of Informatics and Computing