In clinical trials, statistics influence almost every major decision.
From endpoint selection and sample size to regulatory strategy, product approval, and post-market evidence, biostatistics shapes how clinical trials are designed, analyzed, and interpreted.
But for many clinical research professionals, statistics can feel intimidating. It can feel too academic, too technical, or disconnected from the practical decisions that sponsors, CROs, investigators, and clinical operations teams need to make.
Roseann White is a retired biostatistician with more than 30 years of experience across research, development, manufacturing, and clinical research. Her work has included medical device and diagnostic trial designs, statistical analysis plans, FDA interactions, regulatory submissions, and FDA advisory panel support.
In this episode of the Clinical Trial Podcast, Roseann makes biostatistics practical.
She explains what statistical significance does and does not mean, why clinically meaningful results matter, how to think about superiority and non-inferiority, and why sensitivity and specificity are connected rather than separate concepts.
Roseann also discusses why statisticians should be involved early in trial strategy, how financial constraints influence study design, what happens when FDA reviewers disagree with a methodology, and why non-statisticians should ask, “What can go wrong?” before the trial is already underway.
This conversation is for anyone involved in designing, conducting, analyzing, reviewing, or interpreting clinical trials.
What You’ll Learn
In this episode, you will learn:
- What “statistically significant” really means, and why it does not guarantee that a product works
- Why clinical meaning matters just as much as statistical significance
- How to think about superiority and non-inferiority in practical terms
- Why non-inferiority can be useful, and when it may be the wrong design choice
- How sensitivity and specificity are connected in diagnostic testing
- Why ROC curves help show the relationship between sensitivity and specificity
- Why statisticians should be involved early in clinical trial strategy
- How a statistical analysis plan can help avoid confusion later in a trial or registry
- Why endpoint selection should begin with the clinical question, not just the statistical method
- How financial constraints can influence sample size, power, and study design decisions
- Why FDA disagreements should be handled with clarity, humility, and strong explanation
- Why statistical methods should be understandable to both FDA statisticians and clinical reviewers
- What non-statisticians should ask earlier in the trial design process
- Which resources Roseann recommends for people who want to understand statistics better
About the Guest
Roseann White is a retired biostatistician with more than 30 years of experience providing statistical guidance across research, development, manufacturing, and clinical research.
Her work has included medical device and diagnostic trial design, statistical analysis plans, FDA interactions, regulatory submissions, and FDA advisory panel support. She has also worked with companies on clinical trial designs and analyses for regulatory approval and reimbursement.
In retirement, Roseann is focused on helping professionals build a more intuitive understanding of statistics through writing, social media, and volunteer efforts. In the interview, she described this work under the banner of “Humble Statistician.”
