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Artwork for JAMAevidence JAMA Guide to Statistics and Methods

JAMAevidence JAMA Guide to Statistics and Methods

JAMA Network
Clinical Trials
Statistical Analysis
Medical Image Analysis
Deep Learning
Genome-Wide Association Studies
Neural Networks
Machine Learning
Non-Parametric Statistical Analysis
Factorial Clinical Trials
JAMA Network
Immortal Time Bias
AI In Medicine
Target Trial Emulation
Causal Inference
Bayesian Hierarchical Modeling
Randomized Clinical Trials
Dermatology
Ophthalmology
Sequential Multiple Assignment Randomized Trials
Biostatistics

Interviews with authors of JAMA Guide to Statistics and Methods chapters about common and new statistics and methods used in clinical research and reported in medical journals.

PublishesInfrequentlyEpisodes41Founded6 years ago
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Artwork for JAMAevidence JAMA Guide to Statistics and Methods

Latest Episodes

Kendra D. Sims, PhD, postdoctoral associate in Epidemiology, Boston University, discusses Tipping Point Analysis: Assessing the Potential Impact of Missing Data with JAMA Statistical Editor Roger J. Lewis, MD, PhD. Related Content:

• Tipping Point... more

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Edward C. Norton, PhD, University of Michigan Health Management and Policy, discusses Instrumental Variables and Heterogeneous Treatment Effects with JAMA Statistical Editor Roger J. Lewis, MD, PhD. Related Content:

• Instrumental Variables and He... more

YouTube

Jody D. Ciolino, PhD, Northwestern University, Feinberg School of Medicine discusses Factorial Clinical Trial Designs with JAMA Statistical Editor Roger J. Lewis, MD, PhD Related Content:

• Factorial Clinical Trial Designs

• Reporting of Factoria... more

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Maria Mori Brooks, PhD, University of Pittsburgh School of Public Health, discusses "Assessing Unexpected Circumstances That Lead to Modifications in Clinical Trial Design, Conduct, or Analysis" in the JAMA Guide to Statistics and Methods series, wit... more

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Recent Guests

Dr. Kendra Sims
Post-doctoral associate at the Boston University School of Public Health specializing in cardiovascular and cognitive health outcomes.
Boston University School of Public Health
Episode: Tipping Point Analysis: Assessing the Potential Impact of Missing Data With Dr Sims
Professor Edward Norton
An economist and the United Health Care Professor at the University of Michigan, involved in statistical methods and causal inference.
University of Michigan
Episode: Instrumental Variables and Heterogeneous Treatment Effects With Dr Norton
Dr. Jody Ciolino
Associate professor in the Department of Preventive Medicine within the Division of Biostatistics and Informatics
Northwestern University
Episode: Factorial Clinical Trial Designs With Dr Ciolino
Professor Maria Brooks
Professor at the University of Pittsburgh's Department of Epidemiology
University of Pittsburgh
Episode: JAMA Guide to Statistics and Methods: Assessing Unexpected Circumstances That Lead to Modifications in Clinical Trial Design, Conduct, or Analysis With Professor Brooks
Dr. John Lachin
An emeritus research professor of bioinformatics and statistics at the Milken Institute School of Public Health at the George Washington University.
Milken Institute School of Public Health, George Washington University
Episode: Nonparametric Statistical Analysis With Dr Lachin
Andrew Althouse
Senior Principal Statistician at Medtronic, formerly with the University of Pittsburgh School of Medicine
Medtronic
Episode: The Use of Historical Controls in Clinical Trials, With Dr Althouse
Professor William Meurer
Professor of Emergency Medicine and Neurology at the University of Michigan at Ann Arbor, focusing on neurologic emergencies
University of Michigan
Episode: Interim Analyses During Group Sequential Trials With Dr Meurer
Professor Jerry Rotter
Director of the Institute for Translational Genomics and Population Sciences, Professor of Pediatrics and Human Genetics
Lundquist Institute at Harbor-UCLA Medical Center
Episode: Genome-Wide Association Studies With Dr Rotter
Dr. Anna McGlothlin
Director and Senior Statistical Scientist at Berry Consultants
Berry Consultants
Episode: Bayesian Hierarchical Models With Dr McGlothlin

Host

Dr. Roger Lewis
Host and Senior Statistical Editor, known for his expertise in statistics and methods for clinical research, as well as editor of the JAMA Guide to Statistics and Methods series.

Reviews

4.7 out of 5 stars from 51 ratings
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    2 years ago

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Talking Points

Recent interactions between the hosts and their guests.

Tipping Point Analysis: Assessing the Potential Impact of Missing Data With Dr Sims
Q: What are some of the limitations of tipping point analyses?
Tipping point analyses do not quantify the plausibility of a scenario related to missing data and rely on clinical judgment.
Tipping Point Analysis: Assessing the Potential Impact of Missing Data With Dr Sims
Q: Dr. Sims, in your article on tipping point analysis, you lay out some of the challenges that frequently exist when analyzing the results of clinical trials. Can you tell us about those?
Missing data in clinical trials are a significant issue as they often lead to biases when interpreting trial outcomes as those without follow-up may differ systematically from those with available data.
Instrumental Variables and Heterogeneous Treatment Effects With Dr Norton
Q: What do you think are the key takeaways from your article for our listeners?
Understand that while RCTs are ideal, they may not always be possible, and instrumental variables can help tease out causal effects from observational data, acknowledging that these effects may only apply to specific populations.
Instrumental Variables and Heterogeneous Treatment Effects With Dr Norton
Q: How does instrumental variable analysis adjust or account for the fact that some participants' treatments are affected by the instrumental variable and some aren't?
It focuses on the population that is influenced by the instrumental variable, termed 'compliers', to derive relevant treatment effects.
Instrumental Variables and Heterogeneous Treatment Effects With Dr Norton
Q: What is an instrumental variable and what does it allow us to do that we couldn't otherwise do with observational data?
An instrumental variable allows us to create a situation similar to randomization to analyze the impact of treatments in observational data, which would not be feasible in a randomized control trial.

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Focusing on the application of advanced statistical methods in clinical research, this podcast features in-depth discussions with experts who share insights on statistical techniques and methodologies critical for medical studies. Each episode presents varied discussions on topics such as factorial clinical trial designs, instrumental variables, non-parametric analysis, and the ramifications of unexpected events on trial design, illustrating the adaptability required within this field. Additionally, notable examples from real-world case studies enhance the practical understanding of these concepts, making this resource particularly valuable for professionals in health, academia, and medical research.

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this podcast launched 6 years ago and published 41 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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What guests have appeared on this podcast?

Recent guests on this podcast include:

1. Dr. Kendra Sims
2. Professor Edward Norton
3. Dr. Jody Ciolino
4. Professor Maria Brooks
5. Dr. John Lachin
6. Andrew Althouse
7. Professor William Meurer
8. Professor Jerry Rotter

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