RAND Statistics Group Staff Bios

Biostatistics; multiple outcomes; big data; informatics; resampling; multiple hypothesis testing; model selection; diverse data types; longitudinal data; semiparametric and nonparametric methods

Bayesian statistics; multinomial probit models; selection and switching models; latent factor quantile regression; imputation techniques for missing data; quantile regression; and data confidentiality.

Meta-analysis, Statistical programming, Statistics in health, GIS

Bayesian statistics, survival analysis, longitudinal data, shrinkage, multiple imputation

Bayesian statistics, Bayesian nonparametrics, hierarchical modeling, missing data, regression modeling, dynamic distributions

Sampling and survey methodology; quality measurement; experimental design; case-mix adjustment and survey mode effects

Modeling and simulation, statistical analysis methodology

Applied statistics, multiple imputation, non-response, multilevel models, survey design and analysis

Statistical analysis, statistical programming, nonparametric modeling, regression analysis, survival analysis, time series analysis, epidemiology

Causal inference, policy evaluation, machine learning, longitudinal data analysis

Data analysis, education and health applications

Bayesian statistics, hierarchical models, computational statistics, missing data, data integration, Markov chain Monte Carlo, infectious disease biology

Bayesian modeling and simulation, spatial and spatiotemporal modeling, Bayesian causal inference, longitudinal data analysis, multilevel/hierarchical modeling, Stochastic compartmental models, network analysis

Biostatistics; statistical programming; health applications

Regression discontinuity; propensity scoring; experimental and quasi-experimental design; Bayesian methods; item response theory; hierarchical modeling; cross-classified models

Databases and data collection, analysis, and processing; health care quality measurement; statistical analysis methodology

R, SQL, Python, kCCA, PCA, factor analysis, bootstrapping, resampling methods, sample weighting, probabilistic models, hidden Markov chains, hypothesis testing, power analysis, experimental design, kernel-based methods, ridge regression, logistic regression, Poisson regression, propensity scoring, multinomial classification

Survival analysis, causal inference, survey design and analysis, longitudinal methods; machine learning; mapping and spatial analysis

Observational study design, causal mediation analysis, longitudinal data analysis, missing data, balancing weights, semi and nonparametric methods

Program evaluation; instrumental variables and regression discontinuity methods; multilevel models; longitudinal data, imputation methods, and prediction and analysis of latent traits

Non-parametric modeling, clustering and analysis of observational data, sufficient (variable) dimension reduction and its applications

Applied regression, categorical data analysis, survival analysis, epidemiology, statistical programming, cost-effectiveness, health care databases, geographic information systems

Databases and data collection; analysis and processing; survey research methodology; statistical analysis methodology; case-mix adjustment; health care quality measurement