Survival package r bioconductor,emergency kit for family of 5 australia,disaster managements in india,electronic magnetic whiteboard - PDF Review

Survival analysis focuses on the expected duration of time until occurrence of an event of interest. The default graph generated with the R package survival is ugly and it requires programming skills for drawing a nice looking survival curves. Here, we developed and present the survminer R package for facilitating survival analysis and visualization. The current version contains the function ggsurvplot() for easily drawing beautiful and ready-to-publish survival curves using ggplot2. Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. Recently I'm using R survival package to try to predict the probability of people going to churn.

Much appreciate if someone could give me a straight forward explanation (none academic one). You are fitting an Accelerated Failure Time (AFT) model, so all the interpretation should be made in light of this model. Meaning that with the specification that you made you get quantiles of the prediction on the time-scale. Then the question would be why you get negative predictions for some of the quantiles, which seems unreasonable. Not the answer you're looking for?Browse other questions tagged r prediction survival or ask your own question. You must have JavaScript enabled in your browser to utilize the functionality of this website.

However, this failure time may not be observed within the study time period, producing the so-called censored observations. You need also some knowledge in ggplot2 plotting system for drawing a ready-to-publish survival curves.

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