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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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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Statistical Measurement to Compare Risk Tables of Survival Curves

Disclaimer: not a statistician ;-) Background I have time-to-event data and a computational model that generates time-to-event data. The idea is that the modeled data mimics the actual data. I can ...
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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 ...
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Best way to compare mortality in a patient group vs. age and gender-matched control data from CDC life tables?

I have data on the survival of patients from the moment they were diagnosed with a disease, some of whom were treated and some of whom were not. I would like to compare the survival curves for these ...
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Survival (Kamplan-Meier) sensitivity analysis

I conducted a Kaplan-Meier survival analysis to compare survival of 4 groups. The log-rank test yielded a p-value of <0.05. When I conduct pairwise comparisons of the 4 groups (adjusted for ...
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Rejected null hypothesis conclusion, Kaplan-meier curve

What should be the exact way to write the conclusion after the null hypothesis of the log rank test is rejected? I understand that the null hypothesis should be written as there is no difference ...
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Kaplan Meier using survfit confidence interval of the median

In R, I am trying to produce a survival analysis using Kaplan Meier. I have previously used SPSS. I am trying to compare my results but R is producing a 95% confidence level of the median, whereas ...
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Survival Analysis: Quantifying Survival Differences when Proportional Hazards is Violated

I am comparing survival between two groups distinguished by a single factor. The survival curves converge at both ends (near time 0 and near the maximum time) but never cross, and R's survival::cox....
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Survival time analysis, median follow-up time, X-year survival rate

The median follow-up time and the X in X-year survival rate are often far apart in various papers. Is this correct? My personal opinion is that it is good if the Kaplan-Meier survival curve is ...
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Follow-up time with too many zeros?

I have a dataset of 1500 patients for a time-to-event study. Almost half the population died at the moment of inclusion into the study which means that they have had a follow-up time of zero. Now I ...
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Is it possible to calculate conditional PD / unconditional PD from Hazard Rate?

I'm just wondering that can I convert hazard rate to probability of default? Suppose I have the lifetime table data as per below: Time Total Default Non-Default At Risk 0 - - - 356,335 1 5,587 1,...
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I cannot match the results of KaplanMeier and Nelson Aalen by hand

I have fitted both models by using lifelines python library. The results of .event_table from both models are identically matched. However, when I try to ...
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Connecting Survival Analysis to Overall Predicted Survival Probabilities

I've got a question on combining survival analysis with predicted survival probabilities that I'm sure someone must have thought about, but I just can't find anything out there. Imagine I have a good ...
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Use an arbitrary number of features to predict an individuals life expectancy

Objective I want to predict someone's life expectancy (age they will die) based on their lifestyle, current conditions, medications, biomarkers etc. Limitations of supervised learning There are no ...
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calculating power and los follow-up in a study

I have questions about this paper 1 what is the power of this study? what does it mean if lost follow-up more than 20%? why the Kaplan-Meier curve was used beside the cox? Many thnx
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Kaplan-Meier verses Life table method for obtaining cumulative survival properties

Why Kaplan-Meier approach is superior to using the Life table method for obtaining cumulative survival properties?
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Trying to figure out how to explain oscillatory behavior of quantiles from K-M survival analysis when summarizing over many simulated trials

I've been working on simulating survival experiments, and came across what seems to be an odd-looking artifact of Kaplan-Meier analysis which I have been struggling to explain in a concise manner ...
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"Censoring" in survival analysis

All my study patients have complete 1-year follow up for survival. Is it correct to say that the primary outcome measure - survival - was censored at 1 year from diagnosis. Or censoring is only used ...
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Correct y-axis labelling for a Kaplan-Meier figure

Kaplan-Meier curves have been shown with many different names in studies. Survival % survival Survival probability Survival proportion Is it okay to use any of them or are there slight differences? ...
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Selection of patients in retrospective survival analysis?

I had some questions about selection of patients and their time period for a retrospective survival analysis. Let's say we want to perform survival analysis retrospectively on patients who had disease ...
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Kaplan-Meier Subsetting/Selecting Strata for Comparison

When comparing different strata how legitimate is it to merge or eliminate single strata, especially if they represent an intermediate level in order to provide a comparison. Each strata relate to ...
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Survival Curves using Surv and survfit

I have fit a simple KM curve using the Surv and survfit functions in R. The first 6 rows of the data are shown below alongside the code used to obtain the KM curves. ...
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Covariate and Interaction Not Significant When Both in the Model

I am looking at a survival model based on dosing variables, all of which are continuous. I have noticed when categorized, based on Kaplan Meier Curves, that low, medium, high doses behave differently, ...
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Sampling from Kaplan-Meier estimator

I am trying to understand the bootstrapping procedure for right-censored failure time data. One of the bootstrapping methods is based on sampling pairs of failure/censoring times from the non-...
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Cox PH model on 3 groups of same subjects but under varying conditions to see how it affects the survival - should I use clustering?

There's a group of subjects. They experience events depending on (defined by) certain conditions. I was asked by a researcher to perform a sensitivity analysis on 3 different ways to define the ...
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Is the CDF derived from the estimated survival function a valid statistic

Let $S(t)= 1 - F(t)$ be the survival function for the random variable $T$ with CDF $F(t)$. This can be estimated both nonparametrically (via Kaplan-Meier) or parametrically (via Breslow). If we ...
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How to: survival analysis study design

I'm struggling to understand what the correct start date would be for my analysis. I have cross-sectional data for an insurance company and the goal is to perform survival analysis to understand churn ...
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Can somebody please explain where these numbers in survival analysis Life Tables come from?

Specifically, the Cumulative Proportion Surviving at the Time. I've tried reading elsewhere but can't seem to wrap my head around it.
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Can I draw 1-CIF (Cumulative Incidence Function) as a survival curve?

I analyze survival data with competing risks. To me, the CIF is fine, but the researchers want to see how fast the survival falls, so they want the 1-CIF. They know it's NOT the Kaplan-Meier, it's a ...
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Is it possible to create survfit and survdiff objects using imputed data?

I have a dataset in which 45% of participants have missing data. Given the high proportion of missingness, I planned to conduct survival analyses on both an imputed and non-imputed dataset. I am ...
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Calculating number at risk for Kaplan Meier analysis with staggered entry

I am trying to create KM curves in r on data from a telemetry project. The data is right censored and additionally not all individuals were tagged on the same day so they entered the study at ...
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What does the "weights" argument do when fitting Kaplan-Meier curveswith the survival package?

In R's survival package, there is an optional weights argument you can supply when you fit a Kaplan-Meier curve. I can't find any documentation about what this does or what exactly a weighted Kaplan ...
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Censoring for a compount event

I have a data set consisting of patients undergoing a treatment. The data set contains treatment start date, treatment end date, and date of death (if the patient has died). I also have a set of ...
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Survival analysis with only a few time points

I'm investigating the survival of patients with a certain disease, and whether or not they progress to a more severe form of this disease based on several covariates (see EDIT). Currently, I'm ...
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Survival analysis: informative right censored data question

I am attempting to analyze data for someone and am getting stuck on finding something that is appropriate. The design of the experiment is as follows: vials are set up with 10 flies per vial (either ...
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Discrepancy between Kaplan Meier and Cox regression analysis

I want to investigate significant predictors for disease free survival. For this, I did created Kaplan Meier curves for each possible risk factor. The significant predictors after Kaplan Meier ...
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Why are the survival curves different for the Kaplan Meier method and cox regression for the same categorical variable?

I have 1 categorical variable called group (1 = treatment, 2 = placebo). If I create the survival curves with the Kaplan Meier method in SPSS I see that the survival is better for the treatment group ...
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Is the complementary log-log the natural parametrization of the median survival from the KM figure?

When running Kaplan Meier figures and obtaining 95% CIs for quantile statistics, like the median, you usually have the option to supply one of a few possible options for variance estimates. I've been ...
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Kaplan Meier Curve (right censored data)

I have to draw the Kaplan meier curve to show the proportion of clinical trials with and without results (on y-axis) and their time (which is the difference between trials completion and result ...
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2 votes
1 answer
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Stratified KM curve plot for estimation of proportional hazards assumption violation

I am reading a paper that attempts to investigate time varying covariates in Cox proportional hazard model for breast cancer patients. I read that we can plot stratified KM curves for two groups of ...
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Centered Cox survival and Kaplan Meier interpretation with 2 groups

While trying to interpret some of the results I got from the Cox model, I've read that the centered survival curves where you calculate the mean value of each variable is pretty useless but wouldn't ...
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Is it right to join two groups followed in distinct periods of time of the same length in one single Kaplan Meier estimate?

I followed two groups of people for one year. Both were subjected to the same conditions, just in two different periods. One group was followed throughout 2019 and another was followed throughout 2020....
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Would you used prediction from Cox or stratified KM for drawing survival curves and testing them?

Let's assume I have an experiment, where I track some event. I want to analyse the time to this event between two levels of a group G: g1 and g2 I want to do the comparative analysis in sub groups, ...
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1 vote
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Why do my survival curves generated by the Cox differ from Kaplan-Meier for the simplest model?

I was told, that the Cox with a single categorical covariate is equal to the Kaplan-Meier stratified by the levels of this covariate. But the two graphs below don't support it. I also use strata() in ...
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1 answer
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Is doing Kaplan-Meier for 2 curves equivalent to ajdusting for a covarite or stratyfing in Cox? I want the HR for my KM curves

Using the R terminology (but this is software independent statistical problem), is survfit(surv_object ~ rx, data = ovarian) returning 2 Kaplan-Meier curves the ...
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1 answer
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Am I correct in my understanding adjustment for covariate vs. stratyfing by it in the Cox regression?

I'm trying to understand the difference in a Cox model between adding a single categorical covariate like sex = {male, female} and doing stratification by it. I'm not saying about such trivial thing ...
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2 votes
2 answers
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Which method of handling non-proportional hazards (here: crossed KM curves in 2+ points) would you prefer?

I have an experiment, where I compare two groups over time in frames of the time to event analysis. The Kaplan-Meier curves cross 3 times. It means, that the hazards ratios switch to the opposite side ...
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How do I get 1-, 3-, and 5-year survival with survival analysis in SPSS?

I have a database with patients and did survival analysis in SPSS. SPSS gave me the mean and median survivals with 95% confidence intervals. However, I also want the 1-,3-, and 5-year survival times ...
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