Questions tagged [survival]
Survival analysis models time to event data, typically time to death or failure time. Censored data are a common problem for survival analyses.
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Trying to prove Kaplan-Meier statistic with no censoring reduces to empirical survival function
I just started taking survival analysis class and I'm stumped on this question.
We need to show that when there are no censored observations, $\hat{S}(t)=\prod_{t_{(i)\le t}}\frac{(n_i-d_i)}{n_i}$ ...
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Logistic Regression with time slices
I'm using logistic regression to predict student retention in an online course.
I have a data of student interactions within a web platform of an online course. The course spans 6 weeks, with new ...
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Time to Event modeling, fixed but different durations
I am looking at probability of an event ($E$) for a number of customers. Each customer qualifies for the analysis through a qualifying Action ($A$), and has a finite Duration ($D$) to complete Event. ...
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Number of hours instead of frequency count in a chi-squared test
I have a sample where subjects dedicate a variable number of hours to an activity. During these hours, an event might happen. I have a contingency table such as
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How to test relationship between categorical and numerical variables
I have a list of sites and a list of survival probabilities associated with those sites. The data looks like this:
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Finding temporal patterns that predict "life length"
I'm doing research on system usage. It is an online system that provide certain information to users, and I want to predict for how long users use the system. I already noticed that if people don't ...
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Conditional cross-validation sampling
When applying cross-validation to evaluate the predictive performance of a binary classification model, is it acceptable to separately sample from cases and non-cases to achieve class proportions in ...
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Simulation of remission and after remission times under specific conditions
This is basically a data generation problem.
Say, $t$ is an exponential lifetime with mean two years. $tr$ is the remission time and $ts$ is the after remission time. So, $t=tr+ts$. I need to ...
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How to compare two survival percentages for two different populations?
I calculated the 5 year survival of two populations keeping different variable constant each time and got percentages.
I wanted to determine if these percentages were significantly different from each ...
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Cox Proportional Hazards - Dealing with unknown values for factors for some individuals in a population
I'm working on a model with multiple covariates in R. Unfortunately, for one of the factors in the model, the data is spotty and I have a large portion of unknown values. Rouhgly around 30% are NA's. ...
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Nelson-Aalen estimator in discrete time
I was wondering whether the Nelson-Aalen estimator can be applied to discrete-time multi-state data (in months). I ask this because it seems that literature tends to present it only in the continuous-...
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Expected Value of Integral of Stochastic Process
Suppose we have a continuous-time stochastic process $X(t)$, which consists of a sequence of delta functions that, at each time $t$, have a probability $p(t)$ of taking a non-zero value. $p(t)$ lies ...
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How to compare task completion times in a crossover study
Ten participants have completed a task using two different methods A and B. The first five participants completed the task first using method A then B. The remaining participants completed the same ...
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Life expectancy of home appliances
I hope this is the right place where to formulate this question. In a basic course in statistics we learn how to calculate the mean life time of an electronic device. Home appliances are electronic ...
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Segmented time-dependent covariate
I'm performing the cox regression analysis, where I have the model with 1 time-independent (treatment (yes/no)) and 1 time-dependent predictor (blood pressure level).
Outcome is death (yes/no). Time ...
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Problem with lagged covariates
Suppose we have a binary variable $X$ that indicates whether a person ate pizza during the week. This variable is recorded for an entire year. So we have $X_{1}, \dots, X_{52}$ values (1 or 0). ...
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microRNA analysis statistical methodology review [closed]
I am doing a review of statistical methodology used for microRNA data obtained from Affymetrix platform. I have data from 178 patients and their prognosis information as well as recurrence of disease ...
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Protection levels and survival analysis of machinery?
I'm familiar with the basics of survival analysis; we use the cumulative distribution to ask, "What's the probability of a machine still being operable after X days of usage?" Eventually, ...
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How to model the effect of an intervention on survival times?
I have data that includes the survival times as well as the times of an intervention.
I believe that the intervention will shorten survival times i.e. increase the hazard ratio for some time period ...
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Switching the "Event State" with the "Censor State" in Survival Analysis?
Suppose there is a university that has data on different students. The university is trying to build a statistical model that will help them understand which "types of students" (e.g. males, ...
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Hazard function equality $T = \min(T_1, T_2, ..., T_n)$ [closed]
Let $T_i, i = 1, ..., n$ be independent continuous random variables. Denote by $h_i(t)$ the corresponding hazard function of $T_i$. Let $T = \min(T_1, T_2, ..., T_n)$. Denote by $h_T(t)$ the ...
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cox proportional hazard model
am doing my dissertation involving cox model and i would like to understand how you interpret the survival table at mean of covariates. how i do u i determine the survival function from the output
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Book suggestions for survival analysis
I'm trying to learn more about survival analysis and I could really use some suggestions for good texts on the topic. I have a fairly strong background in applied statistical analyses (quantitative ...
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Interpretation of an output from a SURVIVAL ANALYSIS - COX
I am struggling to understand the output of my survival analysis. These are the following codes and outputs:
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How to calculate sample size from hazard ratio?
The marker gene XYX1 being high in breast cancer is associated with poor prognosis with higher hazard ratio : 3.5. I want to calculate sample size with 1 - β (power) = 80%, one sided, type I error? ...
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How to address 'immortal time bias' using R - equivalent to Stata stset?
We have a dataset on cancer patients who have consented to join a study after their diagnosis, which could be months or even years later. After some follow-up, an event occurs. We can fit this data ...
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Why Do We Need Discrete Time Survival Models?
I have been told that one of the main advantages of Semi-Parametric Models (e.g. Survival Analysis, Cox Proportional Hazards Model) is that these models do not require assuming the response variable (...
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In Survival Analysis, does "Non - Cumulative" Hazard Exist?
In the context of Survival Analysis, I have seen that the standard (non-parametric) estimate of the Hazard Function is through the Nelson-Aalen Estimator :
As seen from this formula, the Nelson-Aalen ...
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Why doesn't simulation show KM estimators approach the true survival function?
I'm trying to simulate a survival data with very large sample size and show that the KM estimators approach the true survival function, however it ends up that the two are visually quite different. I ...
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Coefficients in Cox model
The output of coxph has coefficients vector as follows:
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How to translate R to SQL for a Cox Proportional Hazards model?
I have built a cox model in R using the coxph function in the survival package, and now I need to replicate the model in SQL for scoring. From my understanding, the model has the form described on ...
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The coefficient of one variable in Cox regression becames negative when doing multiple variable regression
I am doing Cox proportional regression. I first did Cox regression with only one variable var; its coefficient 0.8752721 was about what I expected and is easy to ...
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Cox proportional hazard model fit to complex survey data
What type goodness-of-fit statistics may be used to evaluate the fit of a cox proportional hazard model to complex survey data?
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Question on Survival Analysis
I'm working on a survival analysis project. In part of the project, I'm asked to "identify factors that may contribute to an increased risk of death". I have difficult time understanding what I'm ...
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Cox model with two time varying independent variables for two legal reforms
I want to perform a proportional hazards model to study if job contracts were affected and became shorter/dismissal was more likely to happen after two labour reforms took place.
I understand that the ...
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Survival analysis - Cox proportional-hazards model problem with output
I have a time to event dataset were I’m looking at the time until individuals perform a specific action. I’m monitoring these individuals for a certain time and if that action is not performed during ...
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Why does survival probabilities not agree?
I'm working with some survival probabilities, and i've gotten kind of confused.
For simplicity, the death rate ( mu(x) ), where x is age in years, are considered constant in intervals of 1 year. In my ...
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Survival analysis: how to determine time at which covariates are obtained?
I'm interested in predicting when a customer will churn, after they've turned a certain age (in this case, age 18, but this could really be any number).
This piece is critical: given the domain being ...
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Using multiple genes building gene signature and survival analysis
This is the paper which is kind of I'm trying to implement based on my set of genes which i have narrowed down from WGCNA analysis.
Its a both conceptual and R related question[How to do it in R] my ...
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How to interpret Cox Proportional Hazards model output when running survival analysis in R?
I have begun studying survival analysis and am using R packages survival and survminer. Verbal descriptions of statistical ...
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Kaplan-Meier survival estimator drop to zero
I am doing survival analysis with KM estimates and one of my curve displays a survival drop to zero:
As I was explained here the drop is here because the last time is an observed event (death) and ...
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Why does manually computed weibull hazard not match formula?
I'm trying to understand survival analysis better and ran into a weird problem with hazard rates - when I calculate it by hand,
i.e. with
$$
h(t) = \left( \frac{ P(T \leq t + \Delta t) - P(T \leq t)}{...
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Balancing "Delayed Entry Bias" and "Survivorship Bias"?
This is a question I have always struggled with - suppose you have medical data on patients over a period of time. This includes information on how long they spent in different states: Admission, ...
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Can some Survival Models "Dominate" other Survival Models?
I recently heard an interesting interpretation of Survival Models : A "standard" Survival Analysis problem (e.g. where at the end of the study, observations can either be "Censored"...
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Does the weight option in coxph function fit the weighted cox regression model?
Suppose I have a survival data with the variables time: follow up time, event: event indicator(1 or 0) with 1 as an event and 0 ...
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Cox model with multiple measures does not recognize the number of IDs?
I am running a survival cox model with multiple measures, here is the code:
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Running a Cox PH Survival Model - univariate vs multivariate model
I am running two Cox Proportional Hazards Models:
Model 1:
survival (1 or 0, with 1 as death) ~ biomarker (high or low)
Model 2:
survival (1 or 0, with 1 as death) ~ biomarker (high or low) + ...
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Is this OK to remove censored observations from the survival analysis and model only those with events, if the number of events is small?
As in the title. If we have a several hundreds of censored data and only a few dozens events, is this OK to remove the censored ones and use the Cox model on those with events only, ignoring the ...
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How to interpret the output of parametric survival regression in python?
I am trying to fit a parametric survival regression for a dataset that I have, I wanted to understand the interpretation of the output of the lifeline package for the lognormal AFT model I have built.
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Calculating hazard using Cox regression
I'm using the Cox regression model in lifelines (python) to try and predict what the probability of a patient surviving X days is given several variables.
Do to some very silly restrictions on the ...