Questions tagged [survival-analysis]

Survival analysis is concerned with modelling the time before subjects change state, typically time until death or failure. One key feature of such data is that they can be censored, that is, some subjects will not have changed state before the study ends.

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How to get the survival duration prediction for each individual in the data by using the Kaplan-Meier method?

I am trying to learn how to use the Kaplan-Meier survival estimator model in the lifelines package. The documentation says that the KaplanMeierFitter.fit function ...
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138 views

Survival Analysis: Pseudo Observation Vs Stratified Cox Regression. Which one is better?

I've been looking into the Cox Regression method for Survival Analysis in Churn Prediction. Cox regression will allow us to determine the probability that a subscriber will unsubscribe after a time $t$...
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Like Time-To-Event analysis, but looking at the timing of events that do or do not happen on a binary outcome

I have a problem where every observation has a binary outcome that occurs at the end of a fixed period, and the predictor variables describe a few types of event that either happen on some day within ...
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What is the best way to model survival when the hazard rate decreases over time?

The standard survival analysis model - for example the model which forms the basis for the proportional hazards model - assumes the hazard rate is constant. In many applications this would be the ...
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CoxPH model with Frailty and L1 regularization

This question stems from an approach proposed by Dr. Silverman, "Predicting Horse Race winners through A Regularized Conditional Logistic Regression with Frailty." In this paper, he proposes ...
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How to do prediction on survival data, using Random Forest

I should make prediction on survival data, using the random Forest method. My question is: should I follow the same approach as in logistic regression? taking into account only the status variable or ...
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22 views

analyze the effect of some new changes to business rules on customers retention and sales

I am trying to analyze the effect of a particular business rule on customer behavior. Background: I have two call centers operating in my company. One is an in-house call center and the other one is a ...
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39 views

Modeling count data with time-dependent rate

For processes of discrete events occurring in continuous time with time-independent rate, we can use count models like Poisson or Negative Binomial. For discrete events that can occur once per sample ...
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25 views

state transition classification on terminal state

I have data on a unit $i$ which enters an entry state $S_0$. This unit has some covariates $x_i$ I would like to predict the probability the unit will reach the terminal state $S_{pos}$ or $S_{neg}$. ...
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36 views

Can i use survival analysis to predict if a person will "die" or not, and then get the survival time if the person does?

I want to determine, given a project, "How long will it take for this project to be successful ?" Therefore, survival analysis seems like a perfect fit in this case (as I do have some projects that ...
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1answer
166 views

Time Series Classification with multiple rows per date

I have a time series data set with the lifecycle of 9000 different B2B sales leads. What I call lifecycle consists of a dataset with one registry per day for every different sales Lead identifier with ...
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191 views

Variable selection methods in survival analysis

I am using two models for my research. One is the coxph regression model and other is survival trees. I have found the scikit-survival package in python which is able to identify contributing ...
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56 views

What kind of algorithm should I use to build ML model that can predict just next reoccurence of an event in the future (at irregular time interval)?

I'm quite new to machine learning and statistics. I've a dataset from some ecommerce sale's history. It's almost 2k instances, and features include personId (string), productCategory (string/...
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493 views

Predicting purchase order?

What is the best option or rather options to predict how much order a customer will place in the future, say next 3 months on a monthly basis. Also will a customer place an order. I used ARIMA to ...
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Inference over a fixed term - what analysis am I doing here?

I have a fixed term of, say, one year. At the end of the term there is an observation of true / false, say a customer either renews or cancels their subscription. This decision is probably based on ...
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29 views

Building a custom scoring function to find mean time-dependent AUC

I’m working on a survival analysis to predict 1-year mortality. I’m trying to build a custom score function that maximizes mean time-dependent AUC. Here is a description of the time-dependent AUC ...
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What is the typical things in Data that i have to look for, when implementing Survival Models using Machine Learning?

Problem Scenario I am working on an industry specific problem focussed on predicting the failure of a seal/gasket in the given time interval(T) in a high-pressure-compression environment. Whenever ...
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Proportional Hazards Assumption - Schoenfeld Residuals X-Axis

I am testing the PH assumption for my COX PH model. Can someone describe what the two x-axis's are in the Schoenfield Residuals plots? One is rank-transformed time and the other is km-transformed time....
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When should I use Cox propotional hazard model, KAPLAN-MEIER’S ESTIMATOR or NELSON-AALEN ESTIMATOR for survival analysis?

I know there is a lot of journal and article about this I have read about it and I don't understand a lot of thing but mainly I don't understand the difference and when to use it.
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11 views

Modelling probability of switching of label from 0 to 1 in next time period for multivariate time series data

I have a data set consisting of unbalanced panel data, i.e. longitudinal multivariate measurements on multiple individuals. I want to estimate a probability that the individual will become 1 in next ...
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Risk analysis on the uptime of web applications (classification? survival analysis?)

I've conducted a couple studies examining how "risky" several web applications are based on whether the respective support teams raise a major incident ticket. The data we have includes the ...
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Measuring chance ("risk") of being in some class

I don't know if this question fits better here or in statistics, but I think here is more appropriate. I have a dataset with several companies and its features and also I have the information if they ...