Guogen Shan

Professor

University of Florida

United States

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Guogen Shan is a Professor at the University of Florida, specializing in neurodegeneration, clinical trial analysis, and adaptive designs in biostatistics. His recent research includes evaluation of socioeconomic factors in combat athletes' neurodegeneration, along with advancements in sample size determination and confidence interval methods for Alzheimer's disease studies. Professor Shan's contributions also extend to innovative designs for multi-arm trials and addressing the progression from mild cognitive impairment to dementia.

Guogen Shan

Research Interests

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Articles (21)

Response to Letter to the Editor “Comments on ‘Novel Non‐Linear Models for Clinical Trial Analysis With Longitudinal Data: A Tutorial Using SAS for Both Frequentist and Bayesian Methods’”

Evaluation of Socioeconomic Disadvantage as a Risk Factor of Neurodegeneration Among Combat Athletes

Adaptive promising zone design for sequential parallel comparison design with continuous outcomes

Closed-form confidence intervals for saved time using summary statistics in Alzheimer’s disease studies

Sample size determination for a study with variable follow-up time

Comparison between treatment-placebo difference and saved time measures to assess treatment effect in Alzheimer's disease

Disease progression from mild cognitive impairment to dementia for patients with Alzheimer's disease or Lewy body pathology

Confidence intervals for overall response rate difference in the sequential parallel comparison design

Score confidence interval with continuity correction for ratio of two independent proportions

ADSS: A Composite Score to Detect Disease Progression in Alzheimer's Disease

Comparison of Pocock and Simon’s covariate-adaptive randomization procedures in clinical trials

Response adaptive randomization design for a two-stage study with binary response

Sparring and the Brain: The Associations between Sparring and Regional Brain Volumes in Professional Mixed Martial Arts Fighters

Two-stage response adaptive randomization designs for multi-arm trials with binary outcome

Promising zone two-stage design for a single-arm study with binary outcome

Continuity Corrected Wilson Interval for the Difference of Two Independent Proportions

New Confidence Intervals for Relative Risk of Two Correlated Proportions

Effects of dose change on the success of clinical trials

Estimation of bias-corrected intraclass correlation coefficient for unbalanced clustered studies with continuous outcomes

Continuity corrected score confidence interval for the difference in proportions in paired data

Conservative confidence intervals for the intraclass correlation coefficient for clustered binary data

Collaborators (4)

Lung-Chang Chien

Gary Cutter

Matthew Peters

Michael Bray

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