2012 John M. Chambers award for best statistical software for our R package, turboEM, which provides a suite of convergence acceleration schemes for EM and MM algorithms (jointly with Jennifer Bobb)
2004 Margaret Merrell award for outstanding doctoral research in Biostatistics. Department of Biostatistics, Johns Hopkins University.
2003 Louis I. and Tomas D. Dublin award for effective use of statistical reasoning and methods in epidemiology. Department of Biostatistics, Johns Hopkins University.
Kalyani RR, Varadhan R, Weiss CO, Fried LP, Cappola AR. Frailty Status and Altered Glucose-Insulin Dynamics. J Gerontol A Biol Sci Med Sci. 2012; 67:1300-1306.
Varadhan R, Weiss CO, Boyd CM. The potential for increasing quality and reducing costs. Ann Intern Med. 2011;155(8):564; author reply 564-5. PMID: 22007054
Weiss CO, Segal JB, Varadhan R. Assessing the applicability of trial evidence to a target sample in the presence of heterogeneity of treatment effect. Pharmacoepidemiol Drug Saf. 2012; 21 Suppl 2:121-9. PMID: 22552987
Kalyani RR, Varadhan R, Weiss CO, Fried LP, Cappola A. Frailty Status and Altered Dynamics of Circulating Energy Metabolism Hormones after Oral Glucose in Older Women. Journal of Nutrition, Health and Aging. 2012; 16:679-686.
Weiss CO, Cappola AR, Varadhan R, Fried LP. Resting Metabolic Rate Among Old-Old Women With and Without Frailty: Variability and Estimation of Energy Requirements. J Am Geriatr. Soc. 2012; 60: 1695-1700.
Puhan MA, Singh S, Weiss CO, Varadhan R, Boyd CM. A Framework for Organizing and Selecting Quantitative Approaches for Benefit Harm Assessment. BMC Medical Research Methodology. 2012; 12:173.
Boyd CM, Singh S, Varadhan R, Weiss CO, Sharma R, Bass EB, Puhan MA. Methods for Benefit and Harm Assessment in Systematic Reviews. Agency for Healthcare Research and Quality. Rockville, MD. Nov 2012. PMID: 23326898.
Varadhan R, Yao W, Matteini A, Beamer B, Xue QL, Yang H, Manwani B, Reiner A, Jenny N, Parekh N, Fallin DM, Newman A, Bandeen-Roche K, Tracy R, Ferrucci L, Walston J. Simple biologically informed inflammatory index of two serum cytokines predicts 10 year all-cause mortality in older adults. J Gerontology Series A. 2014; 69(2):165-73. PMCID: PMC3905766
Kovalchik SA, Varadhan R. Fitting Additive Binomial Regression Models with the R package blm. J Statistical Software. Vol. 54. August 2013
Holmes HM, Min LC, Yee M, Varadhan R, Basran J, Dale W, Boyd CM. Rationalizing prescribing for older patients with multimorbidity: considering time to benefit. Drugs & Aging. 2013. PMCID: PMC3755031
Kuk D, Varadhan R. Model selection in competing risks regression. Statistics in Medicine. 2013; 32(18): 3077-88. PMID: 23436643
Varadhan R, Segal JB, Boyd CM, Wu AW, Weiss CO. A framework for the analysis of heterogeneity of treatment effect in patient-centered outcomes research. J Clin Epi. 2013. PMID: 23651763
Kovalchik SA, Varadhan R, Weiss CO. Assessing heterogeneity of treatment effect in a clinical trial with the proportional interactions model. Statistics in Medicine. 2013;66(8):818-25. PMID: 23788362
Yu T, Fain K, Boyd CM, Singh S, Weiss CO, Li T, Varadhan R, Puhan MA. Benefits and harms of roflumilast in moderate to severe COPD. Thorax. 2013. Dec 17. PMID: 24347460
Varadhan R, Wang SJ. Standardization for subgroup analysis in randomized controlled trials. J Biopharm Stat. 2014. 24(1): 154-67. PMID: 24392983
Weiss CO, Varadhan R, Puhan MA, Vickers A, Bandeen-Roche K, Boyd CM, Kent DM. Multimorbidity and evidence generation. J Gen Intern Med. 2014. PMID: 24442333.
Xue QL, Varadhan R. What is missing in the validation of frailty instruments? J Am Med Dir Assoc. 2014. 15(2): 141-2. PMID: 24405640
Click Here to View Selected Recent Publications
Here are the R packages that I have developed:
SQUAREM: Squared extrapolation methods for accelerating fixed-point iterations.
Algorithms for accelerating the convergence of slow, monotone sequences from smooth, contraction mapping such as the EM algorithm. It can be used to accelerate any smooth, linearly convergent acceleration scheme.
alabama: Constrained nonlinear optimization.
Augmented Lagrangian Adaptive Barrier Minimization Algorithm for optimizing smooth nonlinear objective functions with constraints. Linear or nonlinear equality and inequality constraints are allowed.
optimx: A replacement and extension of the optim() function.
Provides a replacement and extension of the optim() function to unify and streamline optimization capabilities in R for smooth, possibly box constrained functions of several or many parameters.
dfoptim: Derivative-free optimization.
Derivative-Free optimization algorithms. These algorithms do not require gradient information. More importantly, they can be used to solve non-smooth optimization problems.
BB: Solving and optimizing large-scale nonlinear systems.
Barzilai-Borwein spectral methods for solving nonlinear system of equations, and for optimizing nonlinear objective functions subject to simple constraints.
features: Feature extraction for discretely-sampled functional data.
eigeninv: Generates (dense) matrices that have a given set of eigenvalues. Solves the ''inverse eigenvalue problem'' which is to generate a real-valued matrix that has the specified real eigenvalue spectrum. Algorithm can also generate stochastic and doubly stochastic matrices.
turboEM: A suite of convergence acceleration schemes for EM and MM algorithms.
Algorithms for accelerating the convergence of slow, monotone sequences from smooth contraction mapping such as the EM and MM algorithms. It can also be used to accelerate any smooth, linearly convergent acceleration scheme.
anoint: Analysis of interactions
Tools for assessing multiple treatment-covariate interactions with data from a parallel-group randomized controlled clinical trial.
DSBayes: Bayesian subgroup analysis in clinical trials.
Calculates posterior modes and credible intervals of parameters of the Dixon-Simon model for subgroup analysis with binary covariates in clinical trials.
crrstep: Stepwise covariate selection for the Fine & Gray competing risks regression model.
Performs forward and backwards stepwise regression for the proportional subdistribution hazards model in competing risks (Fine & Gray 1999). Procedure uses AIC, BIC and BICcr as selection criteria.