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Biostatistics and Health Data Science

Advanced Statistics Summer Workshop

The Department of Biostatistics and Health Data Science is offering a two week comprehensive summer workshop featuring four courses of advanced statistical topics commonly encountered in medical research. The workshop is tailored for physicians, scientists and researchers actively engaged in biomedical research.

The first two courses will be offered in June 2024. All four courses will be offered in the summer of 2025.

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June 10–21, 2024

In person and via Zoom
Asynchronous attendance allowed

Health Sciences Building (RG) 5000
1050 Wishard Blvd.
Indianapolis, IN 46202

Course Objectives

At the end of the workshop, participants should be able to:

  • Understand and apply advanced study designs across all phases of clinical trials and observational studies.
  • Gain proficiency in advanced statistical models, particularly those used for categorical, longitudinal, and survival outcomes.
  • Gain understanding of reliability and validity assessment methods, and study designs to evaluate such results.
  • Understand key statistical concepts related to causal inference and mediation analyses, and apply these methods effectively in analyzing research data.
  • Acquire knowledge of advanced statistical learning methods for handling high-dimensional data utilized in microarray, sequencing and neuroimaging data analyses.
  • Develop critical statistical thinking through case studies from real-world medical research data.

Course 1: Advanced Study Design

Meet the Instructors


1876-Yiannoutsos, Constantin

Constantin T. Yiannoutsos, PhD

Professor, School of Public Health

Dr. Yiannoutsos focuses on application-driven research, with expertise in diagnostic test validation, sequential models, clinical-trial design, and Bayesian methods. He specializes in HIV/AIDS research, particularly in low to middle-income countries. Dr. Yiannoutsos is the co director of the East Africa Regional Consortium of the International Epidemiology Databases to Evaluate Aids (IeDEA), an international research consortium.

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26956-Zang, Yong

Yong Zang, PhD

Associate Professor of Biostatistics & Health Data Science

Dr. Zang is the Associate Director of the Biostatistics and Data Management Core of the IU Simon Comprehensive Cancer Center. His research focuses on theory, algorithm and software development for adaptive clinical trial design and analysis; statistical genetics.

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2705-Tu, Wanzhu

Wanzhu Tu, PhD

Professor of Biostatistics & Health Data Science

Dr. Tu is an applied statistician who has designed and led multiple clinical trials and observational studies. He has hands-on experience in conducting pragmatic trials. His statistical methodological research is mostly in causal inference, Bayesian inference, and nonparametric regression.

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3770-Li, Xiaochun

Xiaochun Li, PhD

Professor of Biostatistics & Health Data Science

Dr. Li specializes in clinical trials, leveraging longitudinal healthcare data to assess safety and effectiveness of treatments, identification of patient subpopulations for personalized medicine, and riskprediction models for clinical decision support. Dr. Li leads research collaborations in Biostatistical Cores in Cardiology, Emergency Medicine, and Nephrology.

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2775-Monahan, Patrick

Patrick O. Monahan, PhD

Professor of Biostatistics & Health Data Science

Dr. Monahan is the Director of Biostatistics and Data Management Core of the IU Simon Comprehensive Cancer Center. Dr. Monahan’s independent research is in quantitative psychometrics, including latent dimensionality assessment, item response theory, item bias detection, and generalizability theory for reliability assessment. His collaborative research focuses on behavioral medicine and mental health with applications involving analyses of patient-reported symptoms and quality of life across a wide range of disciplines such as primary care, cancer prevention, aging, dementia, psychiatry, diabetes, and juvenile justice.

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2660-Perkins, Susan

Susan M. Perkins, PhD

Professor of Biostatistics & Health Data Science

Dr. Perkins is the Director of the Biostatistics, Epidemiology, and Research Design Program of the Indiana Clinical and Translational Science Institute. Dr. Perkins’ collaborative interests include all aspects of health services research and quality of life research. Her research interests are in the area of categorical data analysis.

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special guest
4992-Kroenke, Kurt

Kurt Kroenke, MD

Chancellor's Professor, IU Indianapolis
Professor of Medicine

Dr. Kroenke is an internationally respected expert in physical and psychological symptoms. He has led or collaborated on more than 15 clinical trials testing collaborative stepped care approaches to managing pain, depression, anxiety, fatigue, and other symptoms. Dr. Kroenke has developed multiple patient-reported outcome measures which have been translated into more than 100 languages and used globally, including the PHQ-9 depression scale, GAD-7 anxiety scale, PHQ-15 somatization scale, PEG pain scale, and P4 suicidality screener. Dr. Kroenke has received numerous awards for both his research and education activities. In 2018, he was the recipient of the Society of General Internal Medicine’s Robert J. Glaser award, the organization’s highest award. He has mentored more than 35 fellows and junior faculty and has over 450 peer-reviewed research publications.

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special guest
portrait of christine caldwell

Christine Caldwell, JD

Regulatory Knowledge and Support Program Manager
Indiana Clinical and Translational Science Institute

Ms. Caldwell advises researchers on regulatory matters including IRB and FDA submissions and manages the CTSI clinical research monitoring service, single IRB project management service, and Scientific Review Committee.

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Workshop Program

June 10–21, 9 a.m.–12 p.m.

Week 1

June 10

9 a.m.

Welcome and introduction Kun Huang, PhD

June 10

9:15 a.m.

Collaborating with Statisticians in Research Kurt Kroenke, MD

June 10

10 a.m.

Clinical Trial Basics Constantin Yiannoutsos, PhD

June 11

9 a.m.

Advanced Trial Design

  • The progression of drug approval
  • Comparative treatment study design
Constantin Yiannoutsos, PhD

June 12

9 a.m.

Advanced Trial Design

  • Group sequential monitoring
  • Case studies
  • Analysis of trial results
Constantin Yiannoutsos, PhD

June 13

9 a.m.

Early Phase Trials

  • Dose finding
  • Dose optimization
  • Adaptive phase II design
Yong Zang, PhD

June 14

9 a.m.

Master protocol trials

  • Basket trial
  • Umbrella trial
  • Platform trial
Yong Zang, PhD

 

Week 2

June 17

9 a.m.

Pragmatic trials

  • Commonly used pragmatic trial designs
  • Analyzing data in pragmatic trials
  • Implementation and reporting
  • Case studies
Wanzhu Tu, PhD

June 18

9 a.m.

Causal inference

  • Counterfactuals
  • Confounding
  • Directed acyclic graphs (DAG)
Xiaochun Li, PhD

June 19

9 a.m.

Psychometric methods

  • Reliability: Domain-sampling, Test-retest
    Interrater
Patrick Monahan, PhD

June 20

9 a.m.

Psychometric methods

  • Validity: Content, construct, factorial, predictive, known-groups, and sensitivity-to-change
  • Design and analysis for assessing reliability and validity of scales that measure psychosocial constructs
Patrick Monahan, PhD

June 21

9 a.m.

Regulatory issues in research studies

  • Institutional Review Board (IRB)
  • FDA processes for drugs, biologics, and devices
  • ClinicalTrials.gov
  • Regulatory issues in protocol development
Christine Caldwell, JD

June 21

10 a.m.

Study implementation

  • Collaborating with biostatistics team
  • Rigor and reproducibility
  • Study design and proposal writing
  • Study start-up and data collection
  • Analysis and dissemination
Susan Perkins, PhD

Course 2: Advanced Statistical Models

Meet the Instructors


2068-Gao, Sujuan

Sujuan Gao, PhD

Professor of Biostatistics & Health Data Science

Dr. Gao is the Director of Biostatistics and Data Management Core of the Indiana Alzheimer’s Disease Research Center. Dr. Gao’s research interest is in developing statistical methods for the analysis of longitudinal, mixed type data. Her major collaborative areas are in Alzheimer’s Disease and aging research.

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1219-Daggy, Joanne

Joanne K. Daggy, PhD

Associate Research Professor of Biostatistics & Health Data Science

Dr. Daggy’s methodological research areas include multivariate modeling of semi-continuous data, latent class models with conditional dependence as applied to the area of record linkage, and joint modeling of medical costs and survival with data from complex surveys. Dr. Daggy’s collaborative research areas include non-pharmacological intervention studies, cancer, and areas in health service research.

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48220-Ren, Jie

Jie Ren, PhD

Assistant Professor of Biostatistics & Health Data Science

Dr. Ren’s research focuses on Bayesian sparse learning, variable selection for high-dimensional data and Bayesian integrative model for multi-omics data. Her major collaborative areas are traumatic brain injury, infectious diseases, genomics and bioinformatics studies.

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4304-Liu, Ziyue

Ziyue Liu, M.D., Ph.D.

Associate Professor of Biostatistics & Health Data Science

Dr. Liu’s collaboration areas include oncology, anesthesiology, kidney stones, HIV, and musculoskeletal diseases. His methodological research focuses state space models, functional data analysis, and time series data analysis. He is mostly interested in understanding complex dynamics over time and utilizing them for classification and forecasting.

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22827-Bakoyannis, Giorgos

Giorgos Bakoyannis, PhD

Associate Professor, School of Public Health

Dr. Bakoyannis’ methodological research is focused on the nonparametric and semiparametric analysis of complex survival, competing risks, and multistate process data, with a special emphasis on issues commonly arising in biomedical and clinical research, such as missing data, misclassification, and interval censoring. His research interests also include methodology development for precision medicine, and in particular, methods for the estimation of optimal individualized treatment rules. His major collaborative research areas are in HIV/AIDS and cancer.

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44484-Zhao, Yi

Yi Zhao, PhD

Associate Professor of Biostatistics & Health Data Sciences

Dr. Zhao’s research focus is on causal mediation analysis, decomposition methods, multi-view data integration, density object analysis, high-dimensional data analysis, neuroimaging data analysis, and proteomics and metabolomics studies. Dr. Zhao has been involved in research projects on neuroscience and pulmonology. Dr. Zhao is a faculty member of the Indiana Alzheimer's Disease Research Center (IADRC) and a faculty member of the Indiana University School of Medicine Alzheimer’s Disease Drug Discovery Center (ADDDC). Dr. Zhao has collaborations in topics of AD, neurodevelopmental impact of substance exposure/abuse, and neurodevelopmental disorders, such as attention-deficit hyperactivity disorder (ADHD) and autism. Dr. Zhao is leading the Pulmonary Biostatistics Core of a large P01 grant and has been involved in research on asthma, cystic fibrosis (CF), and primary ciliary dyskinesia (PCD).

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Workshop Program

June 10–21, 1–4 p.m.

Week 1

June 10

1 p.m.

Review

  • Course overview
  • Basic statistical concept
  • Linear regression models
Sujuan Gao, PhD

June 10

2:30 p.m.

Categorical Data Analysis

  • Binomial and multinomial Inference
  • Two-way tables
  • Statistical tests
Joanne Daggy, PhD

June 11

1 p.m.

Categorical Data Analysis

  • Generalized linear models
  • Logistic regression
  • Loglinear models
  • Mixture models for count data
Joanne Daggy, PhD

June 12

1 p.m.

Longitudinal Data Analysis

  • Mixed effects models
  • Multilevel models
Jie Ren, PhD

June 13

1 p.m.

GEE

Jie Ren, PhD

June 13

2:30 p.m.

Functional Data Analysis Ziyue Liu, PhD

June 14

1 p.m.

Time Series

Ziyue Liu, PhD

June 14

2:30 p.m.

Meta-analysis Sujuan Gao, PhD

 

Week 2

June 17

1 p.m.

Survival Models

  • Survival data, censoring
  • Regression models for survival data
Giorgos Bakoyannis, PhD

June 18

1 p.m.

Survival Models

  • Competing Risk
  • Multi-state models
  • Predictive Accuracy
Giorgos Bakoyannis, PhD

June 19

1 p.m.

Joint Models

Sujuan Gao, PhD

June 19

2:30 p.m.

Statistical Methods for Missing Data

Sujuan Gao, PhD

June 20

1 p.m.

Causal inference

  • Randomized inference
  • Regression Adjustment
  • Propensity scores and matching
Yi Zhao, PhD

June 21

1 p.m.

Mediation Analysis

  • Mediation with single variable
  • Mediation with multiple variables
  • Longitudinal mediations
Yi Zhao, PhD