107 subscribers
Pergi ke luar talian dengan aplikasi Player FM !
Podcast Berbaloi untuk Didengar
DITAJA


Introduction to Dealing with Non-proportional Hazards
Manage episode 451901671 series 2400265
Key points:
- Non-Proportional Hazards: Understanding when and why the proportional hazards assumption fails.
- Hazard Functions: Differences between survival functions and hazard functions; interpreting dynamics over time.
- Data Visualization: Importance of visualizing hazard functions alongside Kaplan-Meier curves.
- Clinical Context: Collaborating with clinicians to understand treatment effects and disease dynamics.
- Effect Quantification: Exploring alternatives to hazard ratios when proportionality doesn’t hold.
- Trial Design: Challenges in designing studies with non-proportional hazards and strategies to address them.
- Simplification Risks: Avoiding oversimplifications like responder analysis or arbitrary sample size increases.
- Stakeholder Communication: Explaining complex survival data effectively to non-statisticians.
- Regulatory Considerations: Balancing valid hypothesis testing with meaningful effect quantification.
- Actionable Insights: Practical steps for statisticians to improve survival analysis and trial design.
Dealing with non-proportional hazards is a complex but critical aspect of survival analysis, and understanding it can make a significant difference in your work. In this episode, Kaspar and I covered everything from hazard functions and survival curves to practical strategies for trial design and effect quantification. If you found these insights valuable, don’t keep them to yourself!
Share this episode with your friends and colleagues who work with survival analysis or clinical trials. And if you haven’t already, make sure to subscribe so you never miss an episode of The Effective Statistician. Let’s work together to elevate the impact of statistics in healthcare!
443 episod
Manage episode 451901671 series 2400265
Key points:
- Non-Proportional Hazards: Understanding when and why the proportional hazards assumption fails.
- Hazard Functions: Differences between survival functions and hazard functions; interpreting dynamics over time.
- Data Visualization: Importance of visualizing hazard functions alongside Kaplan-Meier curves.
- Clinical Context: Collaborating with clinicians to understand treatment effects and disease dynamics.
- Effect Quantification: Exploring alternatives to hazard ratios when proportionality doesn’t hold.
- Trial Design: Challenges in designing studies with non-proportional hazards and strategies to address them.
- Simplification Risks: Avoiding oversimplifications like responder analysis or arbitrary sample size increases.
- Stakeholder Communication: Explaining complex survival data effectively to non-statisticians.
- Regulatory Considerations: Balancing valid hypothesis testing with meaningful effect quantification.
- Actionable Insights: Practical steps for statisticians to improve survival analysis and trial design.
Dealing with non-proportional hazards is a complex but critical aspect of survival analysis, and understanding it can make a significant difference in your work. In this episode, Kaspar and I covered everything from hazard functions and survival curves to practical strategies for trial design and effect quantification. If you found these insights valuable, don’t keep them to yourself!
Share this episode with your friends and colleagues who work with survival analysis or clinical trials. And if you haven’t already, make sure to subscribe so you never miss an episode of The Effective Statistician. Let’s work together to elevate the impact of statistics in healthcare!
443 episod
Semua episod
×

1 Why and how you can promote more students become statisticians 29:32


1 Clarifying confusions around interim, primary, final, and other analyses in clinical trial 31:11


1 Reimagining Clinical Trials with Synthetic Data and Digital Twins 22:11


1 Working in an english work environment as a non-native speaker 12:51


1 R-shiny - how to set it up effectively and avoid common mistakes 26:34


1 3 personal stories of how soft skills have helped me as a statistician 18:39


1 R-packages - best practices and useful tools 20:55


1 Delegating programming tasks - how SOPs help and hinder 17:16


1 Statistics and Market access - from foes to friends 44:23


1 Beyond logic - how to convince others of your ideas 12:52


1 P-value and confidence intervals - the good, the bad, and the ugly 32:31


1 Building the Influence as a Statistician in a Clinical Trial Team 14:10


1 Effective self-management and taking care of your mental health 31:00


1 Taming AI for Biostatistics: Darko Medin on Bio AI Works & Reliable AI Models 28:38


Selamat datang ke Player FM
Player FM mengimbas laman-laman web bagi podcast berkualiti tinggi untuk anda nikmati sekarang. Ia merupakan aplikasi podcast terbaik dan berfungsi untuk Android, iPhone, dan web. Daftar untuk melaraskan langganan merentasi peranti.