# survival analysis

1. ### Sample size calculation for survival clinical trial

Hi! I need to calculate sample size for phase 3 clinical trila with following assumption: Primary Endpoint: Overall Survival (OS) in 36 months; Study Hypothesis: superiority (H0: Υ ≥ δ; H1: Υ < δ); Type I error: 2.5% (α = 0.025); Type II error: 20% (β = 0.2); Expected HR for...
2. ### discrete-time survival analyis vs interval censoring

Dear All, can anyone please explain what the difference is between discrete time survival analysis and interval censoring. I'm wondering if discrete time is a special case of interval censoring where the intervals are regular eg once a year and assesment of event occurence occurs at the same...
3. ### Comparing two survival curves

Hi I have two survival curves/functions given by two sets of data points (t1, P(T>t1)), (t2, P(T>t2) ), ..., (tn, P(T>tn) ) (t1, P*(T>t1)), (t2, P*(T>t2) ), ..., (tn, P*(T>tn) ) where the time points are t1, t2, ..., tn and for each time point I have an estimated probability of survival...
4. ### Calculating Conditional Probability of Survival

I’m looking to analyse a Survival data event relating to lottery draw data. The event being is the time taken for one of the six winning numbers to be drawn again. A table of the data is shown as attached I’d be looking to say, find the conditional probability of this event happening in the next...
5. ### R: Survival and censored data: how structure my input datasheet?

Dear all, I would like to know how to organize the datasheet to import in R for survival analysis (Surv object, logrank test and Coxph). Let's consider an experiment with small animals. A cohort of 600 individuals is being followed-up every two days for 6 days (so I have data at day=0, 2, 4...
6. ### Understanding the difference of using an AFT model and ALT in Predicting Time to Failure

When I started my research in survival analysis, I began to learn about using non-parametric, semi parametric and parametric methods. I was experimenting my data using these approaches. However the examples were mainly coming from the medical domain which has a different kind of data structure...
7. ### interpreting cox proportional test results

Hi, I have attached an image of testing some variables using the cox proportional hazards test in R. Based on the explanation provided in this link https://www.r-bloggers.com/cox-model-assumptions/ it seems to suggest that based on the p-values, that the proportional hazards assumption holds...
8. ### How to determine distribution for failure data?

I am trying to figure out a structured way to deal with failure data. My dataset has about 100 observations of machine life where out of this 100 datapoints, only 40 machines experienced failure during the tests and the remaining is right censored. It also includes several parameters that is...
9. ### Testing for hypergeometric distribution assumption in log rank test

Hi, When using log rank test, there is assumption made on the observations of subjects having reached intended event to be hypergeometric. Is there a way to test this assumption whether it holds true or not and how can this test be done in R or Python given a dataset that has the subjects from...
10. ### Kaplan-Meier Estimator Formula

I am trying to figure out which approach I should use to plot the KM Survival estimator. I am referring to different resources. One from the Survival Analysis Course provided through Coursera and another through a tutorial provided via KDD...
11. ### Survival Analysis-missing time points?

Hi everyone, Im new to survival analysis and I was hoping I could get some help. I am trying to perform survival analysis (time to event) on a year long trial where participants are sampled at multiple time points and I am looking for time of event (infection occurrence) and also for time of...
12. ### Estimating the probability of the residual lifetime based on Kaplan-Meier curve

So I had this question on my exam about survival analysis and I didn't know the answer but I would like to know how I should answer it: "Give, based on this KM-curve, an estimate for the probability that the residual lifetime is larger than 300 days, when the patient is already standing on the...
13. ### Should IRRs and HRs always be equal?

I am running an analysis in a large population registry where individuals enter and leave the dataset at different time points. When i estimated the IRR between two distinct groups and a health outcome, and then a HR, I am finding a small difference (IRR 2.18, HR 2.01). Shouldn't they have...
14. ### Interpreting the COX Model

Am new to Survival Analysis, and am doing this for my Dissertation; The main purpose is to check the survival time to recovery from Severe Acute Malnutrition (SAM). My time event variable is; (1=Recovered from SAM and 0=Event did not Happen). Some of those that were censored included...
15. ### Survival analysis with delayed entries (and left truncation ?)

Hello everyone I have a database starting 01/01/1995 of insured persons some of whom are in a state of disability. I want to calibrate the survival distribution of the population in disability. However, I can not use the data of people with disabilities between 1995 and 2000 (entered and exited...
16. ### Which competing risks survival analysis to choose

Hi guys and girls, First of all, thank you for taking the time to read this and hopefully provide me with an answer. Context: I'm an MD, currently in my third year of my PhD in adult oncology. I'm doing a study regarding treatment-related mortality. In this study, we have roughly 2000 patients...
17. ### Bootstrapping for cox regression analysis

Hello, I have categorical data (high/low) on a protein which I am investigating its potential role as a prognostic utility. I have run a cox regression with the categorical data and 3 year survival as outcome (dead/alive) I get a significant results (attached). I then ran...
18. ### Survival Analysis Alternative for disproportionately missing cases

Hello everyone, I am new to the Data world and am facing a problem which I can’t seem to fix. My task is to analyze why some people cancel their policies and some don’t (find sig. factors) and to estimate the risk of cancelling for different groups. I was thinking of using survival analysis...
19. ### What is the most suitable test for survival data?

I have a data set of two groups of individuals that I want to compare. The data contains who survived and who didn't after 40 days and after 1 year. So this is not a numerical data but a kind of 0/1 data (survive/did not survive). What is the test I should use? Thank you very much, Roy.
20. ### Empirical Survivor Function (esf)

From page 26, chapter 2 of the reference "Tableman, M., & Kim, J. S. (2003). Survival analysis using S: analysis of time-to-event data. CRC press", I have found the definition of the empirical survivor function (esf) is S(t) = (number of individuals > t)/n . But from page 80, chapter 3 of...