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In this video, we will discuss the main concepts behind survival time analysis – easily explained! Survival time analysis is really common in biostatistics. You might have heard of Kaplan-Meier curves, Cox regressions or the log rank test. In clinical trials, survival time analysis is used to compare the performance of two different kinds of treatment, for example. Survival time analysis can also be used to test whether certain characteristics (e.g., smoking, diet, exercise habits, a mutation in a certain gene…) affect the progression of a disease. And as always, you can find the full explanation at biostatsquid.com Hope you like it! https://biostatsquid.com/survival-tim... -------------------------------------------------------------------------------------------------------------------- Watched it already? If you liked this video or found it useful, please let me know! Your comments and feedback are very much appreciated😊 And if you find my content helpful, you might consider buying me a coffee! Any kind of support is greatly appreciated:) https://www.buymeacoffee.com/biostats... If you have questions, don't hesitate to leave me a comment down below, I will answer as soon as I can:) -------------------------------------------------------------------------------------------------------------------- Are you into biostatistics and computational analysis? For more biostatistics tools and resources, you can visit: https://biostatsquid.com/ Follow me on Instagram at @biostatsquid: / biostatsquid For more • simple and clear explanations of biostatistics methods • computational biology tools • easy step-by-step tutorials in R and Python to analyse and visualise your biological data! Don’t forget to subscribe if you don’t want to miss another video from me! -------------------------------------------------------------------------------------------------------------------- Music from #Uppbeat (free for Creators!): https://uppbeat.io/t/pecan-pie/east-s... License code: 80ZOLNQ8NSDSWKFV