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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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Handling 0-day progression in Kaplan-Meier survival analysis

I am considering a survival analysis that examines the time spent between different levels of chronic disease multimorbidity (ML), such as ML1-ML2, ML2-ML3, etc., where MLi represents the presence of '...
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Monte Carlo Sampling for Optimal Replacement Time - Confidence Intervals

Barlow et al. (1960) described a function for optimal replacement time (ORT) estimation $T^*(t) = \frac{C_{P} \cdot S(t)+C_{C}\cdot (1-S(t))}{\int^t_0S(\tau)d\tau}$ where $C_{P}$ is the preventive ...
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Understanding survival curves with time-dependent covariates

In an observational cohort study, I want to assess the impact of exposure to a given prescription drug on mortality. Out of 841,161 patients, 150,279 (17.9%) died during follow-up. Exposure is a time-...
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What assumptions does this Kaplan-Meier thought experiment violate?

I have been thinking about how a naive logistic regression assuming censored subjects were still alive will always overestimate a survival proportion compared to the product-limit estimate, at a ...
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Is differential follow up periods in survival analysis a problem?

I'm looking to compare mortality post-operatively following two different surgical techniques. due to technological advances, one of these surgical techniques was only performed around five years ...
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Diagnosing an unexpected pattern in a survival curve plot

I am conducting a survival analysis (using Cox proportional hazards regression) in R. My overall sample has a ~10% mortality rate, but the Kaplan-Meier survival curves that are derived from my ...
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What are the fundamental differences of Kaplan-Meier testing versus tests of proportions?

Suppose my study will recruit 50 patients and monitor them for some outcome that may crop up at any point in time. My null hypothesis is that the proportion of event-free subjects at time $t=12$ is ...
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Can I extrapolate number of deaths (n_event) from 5-year survival Kaplan Meier?

Let's say there are 52 patients in the negative margin group and 24 in the positive margin group. I'm presented with this statement on the survival rates: "Overall survival was similar in the ...
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Bias introduced by removing early censors

Suppose we have right-censored survival data on some population, and want to compare individuals with "good outcome" (who have no event in the first X months) to individuals with "bad ...
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Difference in survival probabilities at a set timepoint from Kaplan-Meier estimator?

I have a simple survival problem from an RCT, whereby there are two treatment groups (A-control and B-intervention), and the primary outcome is overall survival. We can estimate the Kaplan-Meier ...
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Meta-analysis of Kaplan-Meier survival estimates from one-arm studies

I am writing this topic because there is a statistical problem which does not let me sleep at night. For introduction, I am a clinical researcher interested in niche fields, and many of my projects ...
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determining time points for 75% survival or 25% survival from Kaplan-Meier curve using R

I'm interested in determining the time points for e.g. 75% survival or 25% survival from a Kaplan-Meier curve using R. Take for example the following K-M curve: ...
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Suppose I am using KM curve to estimate S(t) parametrically (say assuming it follows lognormal)

Suppose I am using KM curve to estimate S(t) parametrically (say assuming it follows lognormal). Now this t is in (say) months, and I want to get estimates of the lognormal curve where t is in weeks, ...
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Performing a survival analysis makes sense in this case?

I'm a medical student performing my final degree thesis, so sorry in advance for my little knowledge in stats. I'm performing a retrospective study on the surgical field where I want to evaluate the ...
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Survival analysis with missing values for some variables

I'm performing a survival analysis. I did the univariant Cox regression model for all my variables (about 40). I even performed the univariant analysis in all those variables that had missing values ...
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Which variables I should include in the multivariable Cox regression model?

I'm performing a survival analysis and I have some quantitative variables that I categorized (but I also mantained the quantitative variable for the univariate analysis). For example, I have the ...
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Is the Kaplan-Meier estimator appropriate when I have observed only one event?

Let's say I have a database with 21 patients and one of these patients has died. In such a scenario, can we apply overall survival analysis using the Kaplan-Meier model or no? Meaning that does it ...
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How to interpret Kaplan-Meier curves intersecting at tail end?

I performed a CoxPH analysis on a sample dataset that yielded the following results: Univariate analysis: 0.40 (0.20 - 0.88). P value: 0.02 Multivariate analysis: 0.44 (0.24 - 0.94). P value: 0.03 I ...
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Handling Informative Censored Data in Comparative Analysis of Cumulative Outcomes Across Groups

Hello Cross Validated community, I am working on a dataset that involves multiple groups undergoing a series of interventions, with the aim to achieve a binary outcome (e.g., success or failure). The ...
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Seeking Advice on Combining Kaplan-Meier Curves with Different Observation Periods and Extrapolation

I hope this message finds you well. I am currently working on a research project involving the comparison of Kaplan-Meier curves from clinical trials with different observation periods. The challenge ...
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How to use a Kaplan Meier graph for prediction?

I'm dabbling in survival analysis, applied to cars. I created a survival graph based on age using Kaplan-Meier, in lifelines (python library). However, guidance on ...
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Univariant analysis in survival study

I don't know a lot about statistics and survival analysis so this might be a dull question. I'm performing a survival analysis where I want to study the possible risk or protective factors that could ...
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Retrospective survival analysis censoring

I'm doing a retrospective survival analysis where I evaluate the recurrence of disease after surgery. The problem is that some of the patients don't come again to the clinic after surgery to do the ...
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Comparison of Kaplan-Meier and Cox models for survival analysis

I am looking at the results for survival analysis for leukaemia patients, categorised based on Copy Number Variation (CNV) levels using array comparative genomic hybridisation. So far I have plotted ...
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Sample size estimate for difference of hazard ratios

I'm planning a Kaplan-Meier analysis and need to determine an appropriate sample size for the study. I have two treatment arms and want to show that there is a differential biomarker effect depending ...
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Survivability Analysis whereby study drop put/ censoring indicates a positive result

I am trying to conduct a survivability analysis (particularly a Kaplain-Meier curve) on data for estimating the likelihood of university drop-outs over time. The study began in 2015 (accounting for ...
Luke Jenner's user avatar
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Survival analysis - Kaplan Meier curve suddently drops

I'm doing a survival analysis (where i'm a newby by the way) for churn, to try to understand how long an insurance policy stays "alive". My universe are all policies that were created ...
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Results different using specific years for survival analysis vs zero time starting point

I am using survival analysis to model Treaty ratification, using country-treaty dyads as my primary unit. This means that I have several hundred survival spells covering different time periods (when ...
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Compare median time between different groups and years

I want to investigate whether there is a difference in median waiting time between different groups in different year. I'll try to explain as best I can. My data looks like this: Year Country Waiting ...
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Survival Analysis: adjusting the Kaplan-Meier curve and optimal sample size?

Following the tutorial https://www.youtube.com/watch?v=ujIMPpl2Tr0 from Stanford university, if the log-rank test (a popular test of Kaplan-Meier curves) does not contain report a statistically ...
manuelsokolov's user avatar
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Difference between mean and Kaplan-Meier estimate of mean

I have a panel dataset with individuals on a waiting list for a specific event. The individual can either: still be on the waiting list, have died on the waiting list, be withdrawn from the waiting ...
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Cox-model with exploratory variable measured after start study

I'm working with an unusual dataset, where some of the covariates/characteristics are measured after the start of the study (though without a timestamp!). Basically, it's a dataset about an auction. ...
John's user avatar
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2 answers
209 views

How to compare fitted survival model with covariates vs. Kaplan-Meier?

How would one ideally compare fitted survival models with covariates vs. a Kaplan-Meier with a goal of getting an idea of whether the survival model describes the data well. E.g. in an example like ...
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Interpreting Kaplan Meier Curve

I work for a payments company and have been tasked with answering the following question: what is the likelihood that a customer connects a bank account after the customer's account has been created. ...
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Can I calculate median survival time and its confidence interval using the Kaplan-Meier curve? I don't have available raw data

I am conducting a meta-analysis to compare the differences between Group A and Group B by measuring the pooled Hazard Ratios (HRs) for the median Progression-Free Survival (PFS) and Overall Survival (...
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Testing Proportional Hazards Assumption in Cure model

I am currently working on estimating a cure survival model where I want to incorporate a Cox proportional hazards (PH) model for the latency part of the model (i.e. the part for the observations that ...
John's user avatar
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Difference ACD and Survival Analysis models

Autoregressive conditional duration (ACD) models are typically used in econometrics for dealing with trade duration (TD) data and it is used to capture the clustering structure. In other areas of ...
John's user avatar
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Structural breaks in Survival Analysis

I am currently conducting research using panel data to analyze survival patterns. This involves examining the time-to-event data of a diverse group of participants over multiple years, where the ...
John's user avatar
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2 votes
0 answers
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Should the kaplan meier curve of an training data match the kaplan meier curve from the output of a Weibull AFT model? medians vs rmst

Should the kaplan meier curve of an training data match the kaplan meier curve from the output of a Weibull AFT model? This question is referring to the linked question above. The accepted answer ...
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1 answer
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Choice between Proportional Hazard and Accelerated Failure Time survival models

How can I determine whether to use proportional hazard (PH) or accelerate failure time (AFT) survival models in order to analyze my data? Are there any established guidelines or common practices that ...
John's user avatar
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1 answer
386 views

Using Propensity Score Matching for Kaplan-Meier Survival Analysis

Suppose I have a sample comprising two distinct groups. I want to estimate the survival curve separately for each group using the Kaplan-Meier method. My primary goal is to visualize any differences ...
John's user avatar
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1 vote
1 answer
134 views

Survival Analysis model choice

I am trying to investigate the statistical difference between two groups in my population and exploring suitable survival models for analysis. Let me first outline the data I am working with to ...
John's user avatar
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0 answers
24 views

Survival Analysis where part of population never experiences event [duplicate]

We aim to examine the time it takes for a certain event to happen between two different groups of people in our sample. We are thinking of using survival analysis methods for this purpose. The thing I ...
John's user avatar
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1 vote
1 answer
864 views

Survfit's method for generating the confidence interval of the median survival estimate

The survival package function survfit() calculates a confidence interval for the estimated median survival time. It seems clear ...
fair21comic's user avatar
1 vote
1 answer
76 views

Comparison of an estimated survival probability with a theorical one

My question is relative to the comparison of a probability of surviving at a fixed point in time with a theorical probability of surviving. For example, I have a cohort of patients with cancer ...
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2 answers
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Kaplan Meier but no individuals' data

I did an experiment where I have ten different treatments, with six replicates each. I noted the survival of my animals from Day 4 to Day 12. Each replicate had 12 animals so I noted how many survived ...
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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 ...
Anne's user avatar
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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 ...
Miquel's user avatar
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2 votes
2 answers
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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 ...
Wakeme UpNow's user avatar
1 vote
1 answer
138 views

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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