🔹Clinical Data Analyst Trainee🔹Biostatistician 🔹 Statistical Programmer🔹 Clinical Trails 🔹SAS🔹R 🔹
⏳ What is Survival Analysis? ⏳ 🤔How long does it take to get a job after graduation? Or for a patient to recover from a disease? Questions like these are answered with #SurvivalAnalysis, a statistical approach that makes sense of time-to-event data, even when some pieces are missing! The trickiest part? #Censored data—when we don’t have the full story for every subject. Here’s a quick look at the types: 🚦 Types of Censoring: 📍 Left Censoring: What happened before a certain point is unclear. Example: Students who join a class with prior knowledge. 📍 Right Censoring: We lose track of what happens after a certain point. Example: A participant drops out of a study or can’t be followed up. 📍 Interval Censoring: An event occurs between two moments, but the exact time is unknown. Example: A disease is detected between routine health check-ups. That’s just the beginning! In my next post, I’ll explore how we uncover insights from these challenges and make predictions from incomplete data.🚀 💬 Have you dealt with censored data before? Share your #experience—I’d love to hear about it! #SurvivalAnalysis #CensoredData #DataScience #Biostatistics #Analytics #PHARMASTATS #rstat
