SPEED 2: Statistical Design of Experiments and Sample Size Considerations, Part 1 -- JSM 2025

Active multiple testing with proxy p-values and e-values

8:35 AM - 8:40 AM

Co-authors: Ziyu Xu, Catherine Wang (Carnegie Mellon University), Ziyu Xu, Kathryn Roeder (Carnegie Mellon University), Larry Wasserman (Carnegie Mellon University), Aaditya Ramdas (Carnegie Mellon University)

multiple testing e-values false discovery rate (FDR)active sampling

Adapting Cochran’s sample-size rule to an estimate from a complex sample

8:40 AM - 8:45 AM

Co-authors: Phillip Kott (Semi-retired), Phillip Kott (Semi-retired)

Effective sample size Third central moment Confidence interval Skewness coefficient Clopper-Pearson confidence interval

Adaptive Multi-fidelity Optimization via Online EM with Applications to Digital Design Selection

8:45 AM - 8:50 AM

Co-authors: Wei Dai (George Mason University), Jiayang Sun (George Mason University), Wei Dai (George Mason University)

Digital experimentation ranking and selection online learning

Calculating sample size for methylation sequencing studies

8:50 AM - 8:55 AM

Co-authors: Seth Slettedahl, Seth Slettedahl, Jeanette Eckel-Passow (Mayo Clinic), William Taylor (Mayo Clinic), John Kisiel (Mayo Clinic), Douglas Mahoney (Mayo Clinic)

Methylation Sequencing Sample Size Calculation Binomial Overdispersion

Causal Effects of School Closures on Mental Health During the COVID-19 Pandemic in Ontario, Canada

8:55 AM - 9:00 AM

Co-authors: Jay Xu, Kuan Liu (University of Toronto), Jay Xu, Geoffrey Anderson (University of Toronto)

COVID-19 Mental Health Health Policy School Closures Children and Youth Public Health

Controlling Type I Error Rates for Secondary Endpoints through an Alpha Spending Method

9:00 AM - 9:05 AM

Co-authors: Biju Wang (Johnson & Johnson), Wentao Lu (Southern Methodist University), Biju Wang (Johnson & Johnson)

Overall Type I Error Control Alpha Spending Method Interim Analysis Information Fraction

Deep Learning Survival Analysis for Competing Risk with Functional Covariates and Missing Imputation

9:05 AM - 9:10 AM

Co-authors: Yan Zou (The Cleveland Clinic Foundation), Penglei Gao (The Cleveland Clinic Foundation), Yan Zou (The Cleveland Clinic Foundation), Abhijit Duggal (The Cleveland Clinic Foundation), Shuaiqi Huang (The Cleveland Clinic Foundation), Faming Liang (Purdue University), Xiaofeng Wang (The Cleveland Clinic Foundation)

Competing Risks Discrete-time Survival Deep Learning functional data Missing Imputation Critical care

Enhancing Clinical and Real World Evidence Outcomes: A Macro for Advanced Multi-Block Randomization

9:10 AM - 9:15 AM

Co-authors: Fengzheng Zhu, Fengzheng Zhu

Randomization Techniques Clinical Trial Design SAS Macro Real World Evidence Multi-Block Randomization

Innovations in Accelerating Dose Finding Designs with Backfilling

9:15 AM - 9:20 AM

Co-authors: Frank Shen (BMS), Frank Shen (BMS)

Dose Finding Backfilling Clinical Trials MTD Dose Escalation Seamless Design

Multiple imputation analysis of Miettinen-Nurminen for binary endpoints

9:20 AM - 9:25 AM

Co-authors: Jinhao Zou (Merck), Jinhao Zou (Merck), Qing Li (Merck & Co., Inc.), Jia Hua (Merck), Bin Dong (Merck & Co.)

Missing data Multiple imputation Binary endpoints Miettinen-Nurminen Method Cochran-Mantel-Haenszel Method

Optimal Number of Replicates to Ensure Reproducibility in Pre-Clinical Studies

9:30 AM - 9:35 AM

Co-authors: Shahidul Islam (Biostatistics Unit, Northwell Health, New Hyde Park, NY), Shahidul Islam (Biostatistics Unit, Northwell Health, New Hyde Park, NY), Meredith Akerman (Northwell Health), Sujith Rajan (NYU Grossman Long Island School of Medicine), Chandana Prakashmurthy (NYU Grossman Long Island School of Medicine), M. Mahmood Hussain (NYU Grossman Long Island School of Medicine), Cristina Sison (Biostatistics Unit, Office of Academic Affairs At Northwell Health)

Quantify reproducibility in pre-clinical research optimal number of replications incorporate all replications in data analysis covariance parameter estimates Linear Mixed Effects Model Random Effects

Phase II Decision-Making Framework: Case Studies and Proof of Concept

9:35 AM - 9:40 AM

Co-authors: Taimoor Qureshi (UCSF), Taimoor Qureshi (UCSF)

Bayesian statistics Tuberculosis Clinical trials Decision-making Biostatistics Phase II trials

Power Analysis of Simulated Organ Weight Data

9:40 AM - 9:45 AM

Co-authors: Angela Jeffers, Kathryn Konrad (DLH), Angela Jeffers, Gary Larson, Katherine Allen (DLH), Helen Cunny (Division of Translational Toxicology, NIEHS), Keith Shockley (National Institute of Health)

Statistical power Simulations Effect size Sample size

Reconsidering False Positive Rates for a Portfolio of Carcinogenicity Studies

9:45 AM - 9:50 AM

Co-authors: Kathryn Konrad (DLH), Laura Betz (DLH), Kathryn Konrad (DLH), Shawn Harris (DLH), Katherine Allen (DLH), Helen Cunny (Division of Translational Toxicology, NIEHS), Keith Shockley (National Institute of Health)

False Positive Rate Simulation Carcinogenicity Binary Data

Sample size estimation for the ratio of count outcomes in a cluster randomized trial

9:50 AM - 9:55 AM

Co-authors: Jijia Wang (UT Southwestern Medical Center), Jijia Wang (UT Southwestern Medical Center)

vaccine eﬃcacy cluster randomized trial sample size

Selection Rules for Exponential Population Threshold Parameters

9:55 AM - 10:00 AM

Co-authors: Gary McDonald (Oakland University), Jezerca Hodaj (Oakland University), Jezerca Hodaj (Oakland University)

Weibull Distribution Probability of Correct Selection Minimum Statistic Selection Procedure Means Selection Procedure Subset Size Indifference Zone Selection Rule

Simulation Using Target Trial Emulation For Causal Analysis With Applications to RCT Data for AVM

10:00 AM - 10:05 AM

Co-authors: Michael Machiorlatti (University of Oklahoma Health Sciences Center), Sixia Chen, Michael Machiorlatti (University of Oklahoma Health Sciences Center)

Simulation RCT Causality Target Trial

Statistical graph for the evaluation of the primary endpoint in a clinical trial

10:05 AM - 10:10 AM

Co-authors: Yumi Takagi (Kyoto University), Yumi Takagi (Kyoto University), Takashi Omori, Hiroshi Yadohisa (Doshsiha University)

alternative hypothesis Bayes factor confidence interval function clinical trial primary endpoint statistical graph

SPEED 2: Statistical Design of Experiments and Sample Size Considerations, Part 1

18 Presentations