Doctoral Theses

2023-24

  • Andres Dajles: “Quantifying Model Selection Uncertainty: Bootstrap-Based Measures for Model Comparisons and the Evaluation of Regression Effects in Multimodeling Frameworks” (Advisor: Joseph Cavanaugh)
  • Daren Kuwaye: “Empowering Health Data Insights: Tools for Anomaly Detection and Multivariate Clustering” (Advisor:  Hyunkeun “Ryan” Cho)
  • Ling Zhang: “A Family of Modified Huber Loss Functions for Continual Reassessment Methods in Clinical Trials” (Advisors: Emine Bayman and Gideon Zamba)
    Upon Graduation:  FDA, mathematical statistician
  • Eldon C. Sorensen: “Bayesian Hierarchical Growth Curve Methods with Applications in Linguistics and Audiological Sciences” (Advisor: Jacob Oleson)
    Upon Graduation:  Sandia National Laboratories, R&D statistician
  • Hanh Pham: “Bayesian Latent Space Approaches to Network Analysis” (Advisor: Daniel Sewell)
    Upon Graduation:  Syapse, data scientist
  • Annika A. Helverson: “A Hybrid Particle Filter for Simultaneous Parameter and State Estimation” (Advisor: Grant Brown)
    Upon Graduation: Heluna Health, Research and Evaluation Team
  • Megan E. McCabe: “Impact of Differences in Placebo Response for Platform Trials (Advisors: Emine Bayman and Chris Coffey)
    Upon Graduation:  Assistant Professor of Biostatistics, University of Alabama-Birmingham

2022-23

  • Daniel H.J. Kang: “Efficient Bayesian Adaptive Designs for Oncology Clinical Trials with Multiple Biomarker Subgroups” (Advisors: Christopher Coffey and Jun “Vivien” Yin)
    Upon Graduation: Mathematical Statistical Reviewer, FDA
  • Collin T. Nolte: “What You See is What You Get: A Closer Look at Bias in the Visual World Paradigm” (Advisor: Patrick Breheny)
    Upon Graduation:  Assistant Professor of Statistics, Grinnell College
  • Félix Pabón-Rodríguez: “Bayesian Approaches to Within and Between Host Models for Infectious Disease Processes” (Advisor: Grant Brown)
    Upon Graduation: Assistant Professor, Department of Biostatistics and Health Data Science, Indiana University School of Medicine  
  • Matthew L. Davis: “Thompson Sampling with Smoothing Splines for Hyperparameter Optimization: A Tuning Algorithm that Doesn’t Need Tuning” (Advisor: Brian J. Smith)
    Upon Graduation:  Biostatistician, Medpace (CRO)
  • Scott H. Koeneman: “Probability Distribution Informed Extensions for Classical Model Selection Methods: Moving Beyond the “Rule of 2″” (Advisor: Joseph Cavanaugh)
    Upon Graduation: Assistant Professor, Division of Biostatistics, Department of Pharmacology, Physiology, and Cancer Biology, Sidney Kimmel Medical College, Thomas Jefferson University
  • Helin G. Hernandez: “Bayesian Spatial Modeling of Visceral Leishmaniasis Disease and Infection in Brazil at Multiple Spatial Scales” (Advisor: Jacob Oleson”
    Upon Graduation: RAND Corporation, Associate Statistician
  • Carissa L. Comnick: “Bayesian modeling of Dental Caries Progression Over Time in the Oral Cavity Space” (Advisors: Xian Jin Xie and Brian J. Smith)
    Upon Graduation: United Airlines, Data Scientist

2021-22

  • Nicholas J. Seedorff: “Advancing Flexible Methods for Interpretation and Forecasting of Correlated Data” (Advisor: Grant D. Brown)
    Upon Graduation: Dr. Seedorff is a Data Scientist at Meta
  • Elliot L. Burghardt: “Agglomerative and Divisive Hierarchical Bayesian Clustering with Methods for Longitudinal and Time-to-Event Data.” (Advisors: Joseph Cavanaugh and Daniel Sewell)
    Upon Graduation: Residency in Plastic Surgery Oregon Health & Science University, Portland
  • Monica L. Ahrens:  “Simultaneous Bands for Event Time Percentiles in Cox Models with an Extension to Recurrent Events” (Advisor: Gideon K.D. Zamba)
    Upon Graduation: Dr. Ahrens is a Research Scientist in the Center for Biostatistics and Health Data Science at Virginia Tech University.
  • Melissa N. Jay: “Bayesian methods for estimation and mediation in disease mapping applications” (Advisor: Jacob Oleson)
    Upon Graduation: Dr. Jay is an Assistant Professor of Biostatistics, University of Alabama-Birmingham.
  • Zhuangzhuang Liu: “Assessing the Bivariate Time-Varying Association Between Two Binary Variables Measured at Different Times in a Longitudinal Study” (Advisor:  Hyunkeun “Ryan” Cho)
    Upon Graduation: Dr. Liu is a Senior Statistician at AbbVie, Inc.

2020-21

  • Alexandra M. Curtis: “Subgroup-Specific Dose Finding Using Bayesian Clustering in Phase I-II Clinical Trials” (Advisor: Brian J. Smith)
    Upon Graduation: Dr. Curtis is a research scientist at Eli Lilly and Company.
  • Javier E. Flores: “A New Class of Information Criteria for Improved Prediction in the Presence of Training/Validation Data Heterogeneity”  (Advisor: Joseph E. Cavanaugh)
    Upon Graduation: Dr. Flores is Data Scientist with  Pacific Northwest National Labs in Richland, Washington.
  • Caitlin E. Ward: “Bayesian Methods for Spatio-temporal Epidemic Models to Accurately Capture Complex Dynamics of Disease Spread” (Advisors:  Grant Brown and Jacob J. Oleson)
    Upon Graduation: Dr. Ward is a postdoctoral fellowship at the University of Calgary.
  • Anna C. Reisetter: “Penalized Linear Mixed Models for Structured Genetic Data” (Advisor:  Patrick Breheny)
    Upon Graduation: Dr. Reisetter is a research scientist at Eli Lilly and Company.

2019-20

  • Biyue Dai: “Projection-based Inference and Model Selection for Penalized Regression” (Advisor:  Patrick J. Breheny)
    Upon Graduation: Dr. Dai is a research scientist at Eli Lilly and Company.
  • Anne E. Welhaven: “Pacing Modification by Incorporation of Lag in Early Phase Designs” (Advisors: Christopher S. Coffey and Eric D. Foster)
    Upon Graduation: Dr. Welhaven is a biostatistician at AbbVie, Inc.
  • Brandon D. Butcher: “MCMC Diagnostics for Bayesian Additive Regression Trees and Methods for Flexible Modeling of Predictors” (Advisor: Brian J. Smith)
    Upon Graduation: Dr. Butcher is a statistical scientist at Genentech.

2018-19

  • Qing Li:  “A Two-stage Pseudo-likelihood Approach to Estimation and Inference for Alternating Recurrent Events Data” (Advisor: Gideon K.D. Zamba)
    Upon Graduation: Dr. Li is a Senior Statistician at Takeda Pharmaceuticals.
  • Marie V. Ozanne: “Bayesian Compartmental Models for Zoonotic Visceral Leishmaniasis in the Americas” (Advisors: Grant D. Brown and Jacob J. Oleson)
    Upon Graduation: Dr. Ozanne is assistant professor, Department of Mathematics and Statistics, Mount Holyoke College.
  • Ryan A. Peterson: “Ranked Sparsity: A Regularization Framework for Selecting Features in the Presence of Prior Informational Asymmetry”  (Advisor: Joseph E. Cavanaugh)
    Upon Graduation: Dr. Peterson is assistant professor, Department of Biostatistics and Informatics, University of Colorado-Denver.

2017-18

  • Janel K. Barnes: “Regression and Boosting Methods to Inform Precisionized Treatment Rules Using Data from Crossover Studies ” (Advisor: Jeffrey D. Dawson)
    Upon Graduation: Dr. Barnes is an assistant research scientist in the University of Iowa, Department of Biostatistics, Clinical Trials Statistical Data Management Center.
  • Yiyue Lou: “Principal Stratification: Applications and Extensions in Clinical Trials with Intermediate Variables” (Advisor:  Michael P. Jones)
    Upon Graduation: Dr. Lou is a senior biostatistician at Vertex Pharmaceuticals.
  • Yaohui Zeng: “Scalable Sprase Machine Learning Methods for Big Data” (Advisor: Patrick J. Breheny)
    Upon Graduation: Dr. Zeng is a quantitative analyst at Google.
  • Monelle Tamegnon: “Avoiding the Redundant Effect on Regression Analyses of Including an Outcome in the Imputation Model” (Advisors: Michael P. Jones and Gideon K.D. Zamba)
    Upon Graduation: Dr. Tamegnon is a biostatistician for Johnson and Johnson.
  • Michael Seedorff: “Methods for Testing for Group Differences in Highly Correlated, Nonlinear Eyetracking Data” (Advisors: Jacob J. Oleson and Bob McMurray)
    Upon Graduation: Dr. Seedorff is a quantitative analyst at Google.
  • Natalie R. Langenfeld: “A Novel Sequential ABC Algorithm with Applications to the Opioid Epidemic Using Compartmental Models” (Advisor:  Grant D. Brown)
    Upon Graduation: Dr. Langenfeld is a biostatistician for Nestlé Purina North America
  • Benjamin  N. Riedle: “Probabilistic Pairwise Model Comparisons Based on Discrepancy Measures and a Reconceptualization of the p-Value” (Advisors:  Joseph E. Cavanaugh and Andrew A. Neath)
    Upon Graduation: Dr. Riedle is a research scientist at Eli Lilly and Company.
  • Ryan E. Miller: “Marginal False Discovery Rate Approaches to Inference on Penalized Regression Models”
    (Advisor: Patrick J. Breheny)
    Upon Graduation: Dr. Miller is an assistant professor at Grinnell College.

2016-17

  • Hongqian Wu: “Proportional Likelihood Ratio Mixed Model for Longitudinal Discrete Interval Data” (Advisor:  Michael P. Jones)
    Upon Graduation: Dr. Wu is a Sr. Biostatistician at Novartis Oncology
  • Lixi Yu: “Regularized Efficient  Score Estimation and Testing (RESET) Approach in Low-Dimensional and High-Dimensional GLM” (Advisor: Jian Huang)
    Upon Graduation: Dr. Yu is a statistician at Phastar.
  • Benjamin E. Deonovic:  “MCMC Sampling Methods for Binary Variables with Application to Haplotype Phasing and Allele Specific Expression” (Advisor: Brian J. Smith)
    Upon Graduation: Dr. Deonovic is a research scientist at American College Testing (ACT)
  • Keyla Pagán-Rivera:  “Improved Adjustment for Covariate Measurement Error in Radon Studies: Alternatives to Regression Calibration” (Advisor: Brian J. Smith)
    Upon Graduation: Dr. Pagán-Rivera is a Research Staff Member at the Institute for Defense Analyses.
  • Andrew Ghattas:  “Medical Imaging Segmentation Assessment via Bayesian Approaches to Fusion, Accuracy, and Variablity Estimation with Application to Head and Neck Cancer” (Advisor: Brian J. Smith)
    Upon Graduation: Dr. Ghattas is a Consumer Behavior Modeler, Bank of America, Charlotte, NC
  • David Zahrieh:  “Bayesian Point Process Modeling to Quantify Excess Risk in Spatial Epidemiology: An Analysis of Stillbirths with a Maternal Contextual Effect” (Advisor:  Jacob J. Oleson)
    Upon Graduation: Dr. Zahrieh is a research scientist at the Mayo Clinic-Rochester

2015-16

  • Melissa A. Pugh: “A Bayesian Approach to Detect Time-specific Group Differences Between Nonlinear Temporal Curves” (Advisor: Jacob J. Oleson)
    Upon Graduation: Dr. Pugh is a Research Scientist (Neuroscience Group), Eli Lilly, Inc.
  • John M. VanBuren:  “Integrating Independent Spatio-Temporal Replications to Assess Population Trends in Disease Spread” (Advisor: Jacob J. Oleson)
    Upon Graduation: Dr. VanBuren is an Assistant Professor, Department of Pediatrics-Division of Critical Care, University of Utah
  • Wenjing Lu:  “Monotone Spline-Based Nonparametric Estimation of Longitudinal Data with Mixture Distributions” (Advisors: Jeffrey Long and Ying Zhang)
    Upon Graduation: Dr. Lu is a senior research statistician at AbbVie
  • Fan Tang:  “Structural Time Series Clustering, Modeling and Forecasting in the State-Space Framework” (Advisor: Joseph E. Cavanaugh)
    Upon Graduation: Dr. Tang is a biostatistician with Genentech
  • Ke Liu: “A Joint Model of an Internal Time-Dependent Covariate and Bivariate Time-To-Event Data in Frequentist Paradigm with an Application to MD STARnet Data” (Advisors: Paul Romitti and Ying Zhang)
    Upon Graduation: Dr. Liu is Sr. Biostatistician at Gilead Sciences
  • Patrick P. Ten Eyck: “Problems in Generalized Linear Model Selection and Predictive Evaluation For Binary Outcomes” (Advisor: Joseph E. Cavanaugh)
    Upon Graduation: Dr. Ten Eyck is Assistant Director for Biostatistics and Research Design, Institute for Clinical and Translational Science (ICTS), University of Iowa.

2014-15

  • Grant D. Brown: “Application of Heterogeneous Computing Techniques to Compartmental Spatiotemporal Epidemic Models” (Advisor: Jacob J. Oleson)
    Upon Graduation: Dr. Brown is an Assistant Professor in the Department of Biostatistics, University of Iowa.
  • Spencer G. Lourens:  “Bias in Mixtures of Normal Distributions and Joint Modeling of Longitudinal and Time-to-event Data with Monotonic Change Curves” (Advisors: Jeffrey Long and Ying Zhang)
    Upon Graduation: Dr. Lourens is a Visiting Assistant Professor, Department of Biostatistics, Indiana University
  • Mitchell A. Thomann, “The Flexible Bivariate Continual Reassessment Method ”  (Advisors: Christopher S. Coffey and Eric D. Foster)
    Upon Graduation: Dr. Thomann is an Research Scientist in Biometrics and Advanced Analytics, Eli Lilly, Inc.

2013-14

  • Amy M. Johnson: “Modeling Time Series Data with Semi-Reflective Boundaries” (Advisor: Jeffrey D. Dawson)
    Upon Graduation: Dr. Johnson is an Assistant Professor (Research), Department of Internal Medicine, University of Iowa
  • Knute D. Carter: “Best-Subset Model Selection Based on Multitudinal Assessments of Likelihood Improvements” (Advisor: Joseph E. Cavanaugh)
    Upon Graduation: Dr. Carter is an Adjunct Assistant Professor of Biostatistics and a Research Scientist, Center for Public Health Statistics, University of Iowa
  • Vivien (Jun) Yin: “Bayesian Statistical Modeling of Epidemics and the Contact Networks that Transmit Them” (Advisor: Brian J. Smith).
    Upon Graduation: Dr. Yin is  Assistant Professor of Biostatistics, Mayo Clinic-Rochester

2012-13

  • Eric D. Foster: “State-Space Time Series Clustering Using Discrepancies Based on the Kullback-Leibler Information and Mahalanobis Distance” (Advisor: Joseph E. Cavanaugh)
    Upon Graduation: Dr. Foster is an Assistant Professor of Biostatistics, University of Iowa.
  • Shihao Shen: “Statistical Models for RNA Sequencing” (Advisors: Yi Xing and Jian Huang)
    Upon Graduation: Dr. Shen is Assistant Researcher, Department of Microbiology, Immunology, & Molecular Genetics, UCLA.
  • Elizabeth Dastrup Mills: “Adjusting for Covariates in Zero-Inflated Gamma and Zero-Inflated Log-Normal Models for Semicontinuous Data” (Advisor: Jeffrey D. Dawson)
  • Stephanie A. Kliethermes: “A Bayesian Nonparametric Approach to Modeling Longitudinal Growth Curves with Non-normal Outcomes” (Advisor: Jacob J. Oleson)
    Upon Graduation: Dr. Kliethermes is the Research Director, American Medical Society of Sports Medicine.
  • Tao Zhang: “Discrepancy-Based Algorithms for Best-Subset Model Selection” (Advisor: Joseph E. Cavanaugh)
    Upon Graduation: Dr. Zhang is a Senior Biostatistician at Boehringer Ingelheim, China.

2011-12

  • C. Laura Acion: “Criteria for Generalized Linear Model Selection Based on Kullback’s Symmetric Divergence” (Advisor: Joseph E. Cavanaugh)
    Upon Graduation: Dr. Acion is an Associate Research Scientist, Department Psychiatry, University of Iowa.
  • Mijin Jang: “Working Correlation Selection in GEE” (Advisor: Jane F. Pendergast)
    Upon Graduation: Dr. Jang is Assistant Vice President (Sr. Statistical Modeler), JPMorgan Chase, Chicago.
  • Diqiong Xie: “Bias and Variance Estimators of Average Treatment Effect Using Propensity-score Matching” (Advisor: Michael P. Jones)
    Upon Graduation: Dr. Xie is a biostatistician in the Office of Translational Sciences, Center for Drug Evaluation and Research (CDER), FDA
  • Gang Cheng: “The Nonparametric Least-Squares Method for Estimating Monotone Functions with Interval-Censored observations” (Advisor: Ying Zhang)
    Upon Graduation: Dr. Cheng is a Senior Biostatistician at Boehringer Ingelheim, China.
  • Dingfeng Jiang: “Concave Selection in Generalized Linear Models” (Advisor: Jian Huang)
    Upon Graduation: Dr. Jiang is a statistician at AbbVie.
  • Aaron T. Porter: “A Path-Specific Approach to SEIR Modeling” (Advisor: Jacob J. Oleson)
    Upon Graduation: Dr. Porter is an Assistant Professor in the Department of Applied Mathematics & Statistics, Colorado School of Mines
  • Jingyang Zhang: “Making Diagnosis with Multiple Tests Under No Gold Standard” (Advisors: Kathryn Chaloner and Ying Zhang).
    Upon Graduation: Dr. Zhang is a Staff Scientist at Fred Hutchinson Cancer Research Center.
  • Ming Yang: “Statistical Models for Count Time Series with Excess Zeros” (Gideon K.D. Zamba and Joseph E. Cavanaugh)
    Upon Graduation: Dr. Yang is a Research Associate, Center for Biostatistics in AIDS Research, Harvard University.

2010-11

  • Li Liu: “Grouped Variable Selection in High-Dimensional Partially Linear Additive Cox Model” (Advisor: Jian Huang)
    Upon Graduation: Dr. Liu is a biostatistician at Abbvie.
  • Yu-Hui Huang Chang: “Adaptive Designs for Dose Response Studies” (Advisor: Kathryn Chaloner)
    Upon Graduation: Dr. Chang is a Research Associate, Mayo Clinic Arizona.
  • Lei Hua: “Spline-Based Sieve Semiparametric Generalized Estimating Equation for Panel Count Data” (Advisor: Ying Zhang)
    Upon Graduation: Dr. Hua is Senior Biostatistician at Vertex Pharmaceuticals, Inc.

2009-10

  • Patrick J. Breheny: “Regularized Methods for High-dimensional and Bi-level Viable Selection” (Advisor: Jian Huang)
    Dr. Breheny is an Associate Professor of Biostatistics, University of Iowa.
  • JonDavid Sparks: “Model Selection Criteria in the Presence of Missing Data Based on the Kullback Discrepancy” (Advisor: Joseph E. Cavanaugh)
    Upon Graduation: Dr. Sparks is a statistician at Eli Lilly and Company.
  • Qian Shi: “Bayesian Methods of Evaluation and Use of Surrogate Endpoints in the Single-Trial Settings” (Advisors: M. Kathryn Cowles and Kathryn Chaloner)
    Dr. Shi is an Associate Professor, Department of Health Science Research, Mayo Clinic.
  • Suhong Zhang: “Inference on Association Measure in Copula Model for Bivariate Survival Data with Hybrid Censoring and Application to a HIV Study” (Advisors: Kathryn Chaloner and Ying Zhang)
    Upon Graduation: Dr. Zhang is a biostatistician in the Cardiac Rhythm Management Division, St. Jude Medical Center, Sylmar, CA.
  • Emine Ozgur Bayman: “Bayesian Hierarchical Models for Multi-Center Clinical Trials: Power and Subgroup” (Advisors: Kathryn Chaloner and M. Kathryn Cowles)
    Upon Graduation: Dr. Bayman is an Associate Professor of Anesthesia, University of Iowa.
  • Yiyi Chen: “Optimal Adaptive Group Sequential Design for Phase II Clinical Trials: a Bayesian Decision Theoretic Approach” (Advisor: Brian J. Smith)
    Upon Graduation: Dr. Chen is an Assistant Professor in the Department of Public Health & Preventive Medicine, Oregon Health & Science University.

2006-07

  • Maria C. B. Mendoza: “Case-deletion Diagnostics for Multipoint Quantitative Trait Locus Linkage Analysis” (Advisors: Michael P. Jones and Trudy Burns)
    Upon Graduation: Dr. Mendoza is a biostatistician at the National Center for Toxicological Research.
  • Minggen Lu: “Analysis of Panel Count Data Using Monotone Polynomial Splines” (Advisors: Ying Zhang and Jian Huang)
    Upon Graduation: Dr. Lu is an Associate Professor in the School of Community Health Sciences, University of Nevada-Reno.
  • Zugui Zhang: “Model Selection for Nearly Replicated Data Based on Conceptual Predictive Statistics” (Advisor: Joseph E. Cavanaugh)
    Upon Graduation: Dr. Zhang is Sr. Biostatistician, Christiana Care Health System, Delaware.
  • Huaming Tan: “Variable Selection and Estimation in the Partially Linear AFT Model” (Advisor: Jian Huang)
    Upon Graduation: Dr. Tan is Director of Biostatistics at Pfizer.

2005-06

  • Bongin Yoo: “Estimation and Design Considerations in the Mixed Effects Cox Regression Model” (Advisor: Michael P. Jones)
    Upon Graduation: Dr. Yoo is Senior Research Biostatistician, Bristol-Myers Squibb.
  • Wei Zhang: “Analysis of Doubly Censored Survival  Data with Applications to GBV-C and HIV Studies” (Advisors: Kathryn Chaloner and Ying Zhang)
    Upon Graduation: Dr. Zhang is Regional Head of Biometrics and Data Management, Asia/MENA, Boehringer Ingelheim Pharameceutials.
  • Kwang-Youn A. Kim: “Statistical Methods for Detecting Positional Correlation of Expression and Genetic Interactions with eQTL Data” (Advisors: Jian Huang and Val Sheffield)
    Upon Graduation: Dr. Kim is an Assistant Professor, Feninberg School of Medicine, Northwestern University.

2004-05

  • Deli Wang: “Robust Estimation of a Two-way Semilinear Model with Applications to Microdata Normalization and Analysis” (Advisor: Jian Huang)
    Upon Graduation: Dr. Wang is a research statistician at Abbott Laboratories.
  • Xinqun Yang: “The Posterior Probability of Linkage Allowing for Linkage Disequilibrium and a New Estimate of Disequilibrium between a Trait and a Marker ” (Advisors: Jian Huang and Veronica Vieland)
    Upon Graduation: Dr. Yang is a Senior Manager, Biostatistics at Amgen.
  • Xian-Jin Xie: A Goodness-of-Fit Test for Logistic  Regression Models with Continuous Predictors” (Advisors: William R. Clarke and Jane F. Pendergast)
    Upon Graduation: Dr. Xie is a Professor in the Department of Clinical Sciences, Simmons Comprehensive Cancer Center, University of Texas-Southwestern.

2002-03

  • Wenquan Wang: “Estimating and Testing Treatment Effects on Two Binary Endpoints and Association Between Endpoints in Clinical Trials” (William R. Clarke and Robert F. Woolson)
    Upon Graduation: Dr. Wang is Senior Manager, Biostatistics, Eisai, Inc.

2001-02

  • Farideh Dehkordi-Vakil: “A Bayesian Method for Estimating Smooth Monotone Functions” (Advisor: Geroge Woodworth)
    Upon Graduation: Dr. Dehkordi-Vakil is an Associate Professor of Decision Sciences, Western Illinois University.
  • Sheela Kolluri: “A Model for Longitudinal Poisson Count Data with Informative Dropout” (Advisor: Michael P. Jones)
    Upon Graduation: Dr. Kolluri is a biostatistician, Pfizer-Groton Laboratories.
  • Chandan Saha: “Quantifying the Asymptotic Bias in the Linear Mixed-Effects Model Under Informative Dropout, Drop-In and Other Missing Data Patterns” (Advisor: Michael P. Jones)
    Upon Graduation: Dr. Saha is Associate Professor of Biostatistics, Indiana University School of Medicine.
  • Brian J. Smith: “A Bayesian Framework for Analyzing Exposure Data from the Iowa Radon Lung Cancer Study” (Advisor: M. Kathryn Cowles)
    Dr. Smith is Professor of Biostatistics, University of Iowa.
  • Jeff M. Allen: “Frequentist Performance of Bayesian Models for Bivariate Longitudinal Data with Two Informative Drop-Out Times” (Advisors: M. Kathryn Cowles and Michael P. Jones)
    Upon Graduation: Dr. Allen is a statistician at American College Testing (ACT).