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- 82% Survival Analysis in R

Survival Analysis in R

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8.2/10 (Our Score)
Product is rated as #41 in category R

Survival Analysis is a sub discipline of statistics. It actually has several names. In some fields it is called event–time analysis, reliability analysis or duration analysis. R is one of the main tools to perform this sort of analysis thanks to the survival package.

In this course you will learn how to use R to perform survival analysis. To check out the course content it is recommended to take a look at the course curriculum. There are also videos available for free preview.

The course structure is as follows:

We will start out with course orientation, background on which packages are primarily used for survival analysis and how to find them, the course datasets as well as general survival analysis concepts.

After that we will dive right in and create our first survival models. We will use the Kaplan Meier estimator as well as the logrank test as our first standard survival analysis tools.

When we talk about survival analysis there is one model type which is an absolute cornerstone of survival analysis: the Cox proportional hazards model. You will learn how to create such a model, how to add covariates and how to interpret the results.

You will also learn about survival trees. These rather new machine learning tools are more and more popular in survival analysis. In R you have several functions available to fit such a survival tree.

Instructor Details

R-Tutorials is your provider of choice when it comes to analytics training courses! Try it out our 100,000+ students love it. We focus on Data Science tutorials. Offering several R courses for every skill level, we are among Udemy's top R training provider. On top of that courses on Tableau, Excel and a Data Science career guide are available. All of our courses contain exercises to give you the opportunity to try out the material on your own. You will also get downloadable script pdfs to recap the lessons. The courses are taught by our main instructor Martin trained biostatistician and enthusiastic data scientist / R user. Should you have any questions, you are invited to check out our website, you can open a discussion in the course or you can simply drop us a pm. We are here to help you boost your career with analytics training Just learn and enjoy.

Specification: Survival Analysis in R

Duration

4 hours

Year

2019

Level

All

Certificate

Yes

Quizzes

No

13 reviews for Survival Analysis in R

4.5 out of 5
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  1. Daniel Lee

    still have no received any responses to my questions. overall, one can use this course to get started in conducting survival analysis (or interpreting its results). it builds a decent foundation but analysts should supplement this course with additional reading from a textbook or university level course to develop a more comprehensive understanding of survival analysis.

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  2. Marietta Kokla

    everything so far being explained very well

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  3. Maya S

    This course forms a good introduction to survival analysis with clear and easy to follow instructions. The practical examples adds value to really understand the results and how to interpret them.

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  4. Yuval Levy

    Does a great job in delivering the technicalities with just the bare minimum for the math part. Excellent for those who want the into for the subject with not to much theory. Does the job.

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  5. Sebastian Radynski–Figlarz

    Tak. Potem oceni dok adniej kurs. Podoba mi si e rozumiem go cia, wszystko profesjonalnie opisuje i na grafice, i s subtitles, wszystko fajnie.

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  6. Sebastian Radynski Figlarz

    Tak. Potem oceni dok adniej kurs. Podoba mi si e rozumiem go cia, wszystko profesjonalnie opisuje i na grafice, i s subtitles, wszystko fajnie.

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  7. Jennifer L

    Great course, I’m following along with my own project. I’ve done a lot of survival analysis courses and I think this is the best one.

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  8. John King

    Very practical and useful tutorial on time to event analysis in R

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  9. Daniel Hoffmann

    very comprehensive good structure, well presented and nicely designed presentation! Recomended!

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  10. Hemakshi M Bhargava

    Perfectly explains the non parametric, semi parametric and parametric models! Could include a little interpretation of the parametric models!

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  11. Clifton Baldwin

    So far, I am really happy with this course. It meets my expectations (which is why I did not rate a full 5 stars of above expectations.)

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  12. Naga Saritha Kolli

    yes exactly. It helped me a lot.

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  13. Ammar Abdelghany

    Very nicely explained!

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