Questions tagged [kaplan-meier]
The Kaplan-Meier estimator is a common non-parametric method for survival analysis and for plotting survival graphs. The survival function $S(t)$ calculates the probability of survival past time $t$. It is most useful in comparing the survival of different groups while properly handling censored data.
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Cox PH - Ph assumption met or no
Im currently working on a data set and I can not get my statistics to add up. It is a survival analysis and I'm using Kaplan-Meier and Cox proportional-Hazards regression. I have used STATA for ...
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ANOVA or survival analysis in this experiment?
I have performed the following experiment but I am not sure what statistical analysis perform.
The aim is to test if a drug is lethal on a fish species. For this, I have 3 tanks with 10 fish in each ...
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How to deal with noisy observation in Survival Analysis
I'm new to Survival Analysis. Usually in survival analysis, we want to model the survival function progress w.r.t time. This is normally done through Cox model, or KM-model within a specific time ...
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How to generate multiple forecast simulation paths for survival analysis?
I am trying to create R code for generating multiple simulation paths for forecasting survival probabilities. In the code posted at the bottom, I take the survival ...
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Kaplan-Meier plots as feature selection method?
Can Kaplan-Meier plots be used for feature selection when building a multivariable survival model (e.g. Cox PH)? Would a visual assessment (no separation/crossing curves) suffice or would it have to ...
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Analyses of continuous variable like time to event within clinical setting
My apologies if this has been previously answered.
I am fairly new to statistics of clinical trials and I want to know how the expert statisticians handle continuous variables like "time to event&...
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How to code survival data so that sarting survival is below 1
I am analysing the time to the end of rehabilitation; however, not all patients receive rehabilitation. Therefore, for making Kaplan-Meier curves for the whole study population (including non-...
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Calculate Inverse Probability Weights for Kaplan-Meier survival curves in R
I am analysing HR data where event is leaving (so right-censored and many more survivors than not). My Kaplan-Meier survival curves all look like this (and many of them wilder, so Cox is not an option)...
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All Survival Coefficients of Cox proportional-hazards model are close to 0
I am using Cox proportional-hazards model to study which of my activity variants make people bored of the website all together.
My data consists of few hundred rows. Each row contains the following ...
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Kaplan-Meier survival graph explanation
I have used gepia2 site to look for survival associated with genes I output something like this
I understand this part which is Logrank p value which shows PTDSS2 gene high and low group have survival ...
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Competing risks time-to-event analysis
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I have a time-to-event scenario where I want to look at Covid19 patients.
I want to analyse how long it takes before they are extubated (taken off ventilator) in two different treatment groups. ...
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Interpretation of Log-rank test with "close" survival curves
I have a question about the interpretation of the log-rank test, when the survival curves (in the figures below hazard curves) are close together.
Below you can find two figures with survival curves ...
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How to maximize survival rates, given one variable? (in R)
I'm a radiation oncologist. I have a list of patients. For each patient, I have
D = dose received (in Gray)
T = date of death or last check-up date
S = status (0=alive, 1=dead)
I have 5 years of ...
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Is it possible to add age to survival time for a KM-curve?
In a cohort study we are studying disease X with subtypes A, B, C.
When one of these subtypes occurs, the occurrence other subtypes is precluded, therefore I have ran a competing risk regression with ...
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Sanity checking survival model
I have some basic statistics foundations (Lean Six Sigma, Industrial Engineering in College), but I'm completely new to survival analysis, and relatively new to Data Science. So I'm looking to sanity-...
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Does survival analysis require you to split the data?
I have some data which I'm using to predict the potential outcome of a new applicant defaulting on their credit loan.
For Kaplan-Meier, I don't believe there would be a need for splitting the data as ...
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Kaplan-Meier / NPMLE / semi-parametric ph survival curve troubleshooting
I've got my survival curves looking like this:
NPMLE using icenReg
semi_parametric using icenReg
and cox PH, where right side of interval is used as time of event
Why do the survival curves ...
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Why does CoxPH always underperforming vs a simple Kaplan Meier?
For context, my company have outsourced a lifetime prediction to a big firm. The goal is to predict lifetimes of a categorical variable.
The data includes customers from 2012 to 2022. I have the ...
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Survival Curve probability interpretation?
Once I've plotted the survival rate distribution(s) for, let's say, heart failure patients,
Are survival rates applicable to ANY new person coming in and simply being predicted based on the day they ...
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Methods to estimate bivariate survival function under *bivariate* censoring
I am looking at the relation between two time-to-event variables subject to censoring. The seminal work from Lin and Ying is unfortunately paywalled (https://www.jstor.org/stable/2337178), but I ...
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can I compare failure rates of two appliances in case I do not have an equal number of each?
I am a student working on an original article about oral appliances that are place after the extraction of primary teeth in children. there are two variants of these appliances, fixed and removable.
I ...
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Can we compute predicted cumulative incidence after fitting a Cox model?
After fitting a Cox regression, we can compute the predicted survival curve S(t) e.g.
in R:
survfit(formula, newdata, ...)
where formula is a coxph object.
With the KM estimate, cumulative incidence ...
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Survival analysis: censoring data with certainty of event not occuring?
I have data that I think can be best analysed using a survival analysis.
I have bumblebee colonies that need to grow to a certain threshold size for them to become sellable to greenhouse growers. I ...
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Basic Kaplan-Meier survival analysis input data interpretation with discrete time periods
I am trying to apply Kaplan-Meier survival analysis from the Reliability package in Python to a problem with discrete time periods, and I'm having some trouble understanding which periods to list ...
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Good resources for visualizing time-to-event(s) data where event is a continuous variable
I am analyzing patients' rehabilitation use over a 5-year period. Describing their rehabilitation is challenging since:
I should describe the proportion excluded from rehabilitation (zero-inflatation)...
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Kaplan-Meier curves for plotting the start AND end of something
Kaplan-Meier curves are effective for showing end OR start of something in time. Would it be possible to use them for showing both: end and start? Any examples of such figures? Thus, the figure should ...
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How does using log transformation for a confidence interval of the survival stabilizes variance?
I only found that it eliminates the estimator of survival from the variance formula, but could anyone show some references or write a few formulas to show how exactly the Greenwood becomes more stable ...
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How to obtain a confidence interval for the cumulative incidence (1-KM) via "log" formula?
I want to show the "mirror" to the survival probability calculated with the Kaplan-Meier estimator, that is the cumulative incidence (or probability).
I would like to add the pointwise ...
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Kaplan-Meier-type curves for continuous covariates
It's well known the Kaplan-Meier curve is a univariate time-to-event summary plot. If you want to show differences between groups, you can make a KM curve for each group. In addition you can calculate ...
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Right censoring in survival analysis
I work with data at an union. If you are member while studying your monthly fee is 0 or a small amount depending on the type of membership. When you end your studies the fee increases significantly ...
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In survival analysis, can the last follow up date be with a different specialty
I'm interested in collecting the date follow up for patients with cancer of the uterus. it's retrospective chart review. Can the date of last follow up include visits to different specialties or it ...
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Kaplan-Meier estimator when no censoring
I am looking at the Kaplan-Meier estimator of the survival function when we have no censored observations. Let $$\hat{S}(t) =\begin{cases} 1,&\quad t<t_1, \\
\prod_{t_i\le t}[1-\frac{d_i}{Y_i}]...
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The link between log-rank test and KM estimates
I have taken the survival analysis class a few years ago, and we have learned both Kaplan-Meier estiamtes for survival curves, and the log-rank test for inferencing the difference of hazard rate ...
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Simulating Survival Times and Accounting for Population Mean Linear Predictor?
I have been using the methods outlined in: Bender, Ralf, Thomas Augustin, and Maria Blettner, "Generating survival times to simulate Cox proportional hazards models," Statist. Med. 24: 1713–...
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Adjust Kaplan-Meier Curve Given Cox PH Coefficient?
I have a survival dataset that I'm working with in R. I can generate a KM curve and also a table of survival and time values.
My question is, given a point on the survival curve (let's say 0.8 ...
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How to create KM curves with time-dependent covariate
Some patient received an treatment as treated group and some did not as control group. In order to consider "immortal time bias", I coded the treatment as a time-dependent covariate. Could ...
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Kaplan Meier (KM) estimator and non independent observations
I have to deal with a statistical issue in a study, specially with the use of Kaplan-Meier estimator in the case of non independent observations.
Background of the study:
We follow-up patients (N = ...
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Interpretation of interaction between variable and time in cox regression
I was running a model to check the survival rate among different treatments. Basically, the treatment has four groups. I firstly plot a K-M curve and noticed clear interactions among the four ...
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Variable entry times for survival analysis
I'm analyzing Trisomy 18 patients who underwent cardiac surgery. They all had surgery at different points in time, and they have all been followed-up until present day. This means that follow-up times ...
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Likelihood of a censored data vs. likelihood based on IPCW weights
I was wondering if there is a relation between the classical form of the likelihood when we have censored observation : i.e
Let's define $T_i = \inf(X_i,C_i)$ and $\delta_i = \mathbb{1}_{X_i \leq C_i} ...
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Draw survival curves of 2 groups after multiple imputation on covariates
I wonder how to draw survival curves (Kaplan-Meier) when there is no missing information on the survival variables but on the stratification covariate.
For example, we know for all patients the follow-...
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Variance of Kaplan-Meier estimator
Here and here and on the Wikipedia page it is stated that for estimating the variance of Kaplan Meier estimator $S(t)$ using delta method one can use the fact that: $$Var(log\hat{S}(t)) \approx \frac{...
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How to conduct Cox-regression with time-dependent covariate and estimate K-M plots (including log-rank test)?
I want to conduct a Cox-regression with time-dependent covariate and other control variables and estimate K-M plot with log-rank test result. I will take the heart transplant as an example, some ...
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Multi-centre survival analysis
I have question regarding survival analysis. I am looking at observational studies comparing patient survival who received treatments A or B at different centres (>10), for the same condition and ...
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Kaplan-Meier curves for retrospective studies
While doing a review i noticed that Kaplan-Meier curves are often used for retrospective studies in the medical field.
However, is it correct to do so even if the registry of data is not prospective? ...
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upper confidence interval limit are NA for median overall survival
I have survival data set and had issue of getting upper 95 % confidence interval for median overall survival. I had observed other users had similar issue and I went through all suggestion. However, ...
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Survival analysis mostly censored data
I have (another) question regarding survival analysis: If I had two groups of participants (rather small, less than 100, well-matched apart for one or two covariates) exposed to treatments A and B ...
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If there is no censoring, can be the naive 3rd quantile different from the one calculated with from the Kaplan-Meier?
I know, that the median survival time calculated from the Kaplan-Meier estimator is equal to the "naive" descriptive median of the survival time when no censoring in data occurs.
Does it ...
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How can we build a probability censoring function such that the survival function of Kaplan Meier will not be effected?
If i have the complete data of a subject (un-censored), How can I design a probability function for censoring the data such that the survival function value will not change?
What is the condition for ...
