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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A doubt on conditional random variable
We are working for two component systems, where first component failed before threshold $s$ and second before $t$.
Let $(X_1,X_2)$ be a non-negative, absolutely continuous random vector with ...
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Subject Interdependence and Shared Shocks in Survival/Duration Analysis
To preface, I definitely need to conduct more research on my own. But also asking for those that are curious in the future.
Firstly, I was wondering what topics of survival analysis I should look into ...
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Does violation of PH in one covariate bias the coefficients of other covariates in a Cox model?
When a categorical covariate violates the proportional hazards (PH) assumption, a common recommendation is to use a stratified Cox model by putting that variable in ...
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Should I standardize or only center "Age" in an ordinal semiparametric regression model?
I am using Ordinal Semiparametric Regression (Frank Harrell's rms package) to model overall survival in patients with brain tumor. I am thinking of centering the Age covariate, because I want Age = 0 ...
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interpretation cox regression interaction and spline
I did a regression on the duration of unemployment in months. Proportional hazards assumption wasnt met which is why I split the data at 16 months. I also interacted the dummy category female with ...
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Weighted quantile sum (WQS) and Cox model
I am working on weighted quantile sum (WQS), and I know that the WQS index obtained represents the effect of the mixture on my outcome.
In order to know which effect the mixture has on my outcome in ...
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How to decide if the inclusion of a variable violates the Markov property?
My question assumes the following set up for continuous time discrete space:
Consider $n$ individuals indexed by $i = 1, \ldots, n$. For each individual $i$:
$Y_i(t) \in \{1, 2, \ldots, k\}$ denotes ...
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ordParallel() errors in rms::orm models: rfort(theta) : NA/NaN/Inf and argument is of length zero depending on sample size / model complexity
I edited the question to open it again because my main question is how to solve this issue statistically since I cannot interfere with the numerical analysis of the program.
I’m working with ordinal ...
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When to ignore violated proportional hazards assumption in Cox PH models?
I am using Cox Proportional Hazards Regression to model overall survival in patients with brain tumor. The proportionality assumption is violated, but I am wondering when it is okay to ignore the ...
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Understanding and interpreting Cox Regression when using ordered factors
I am trying to understand ordered factors (polynomial terms) and their interpretation in Cox Proportional Hazards regression model. I know when using lm() to fit ...
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What is the best statistical approach to forecast cash flow from run-off debt vintages with a growing balance?
community.
I'm facing a modeling problem for cash flow forecasting and would like to know what the most robust mathematical/statistical approach is to solve it.
The Problem: Debt Recovery Forecasting
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Modelling short vs. longterm unemployment duration
I am a student of sociology and for my thesis I plan on comparing factors of the duration of short term (12 months and less) vs. longterm unemployment (more than 12 months of continuous unemployment). ...
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Estimating hazard function from the Nelson-Aalen estimator
According to page 166 of Klein and Moeschberger, $\Delta \tilde{H}(t_i)$ provides a crude estimator of $h(t)$ at the death times, where $\Delta \tilde{H}(t_i) = \tilde{H}(t_i) - \tilde{H}(t_{i-1})$ ...
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Are there any statistical methods to analyse whether one distribution is left-truncated compared to another distribution?
I have a data set where several individuals have been measured for a continuous variable A.
A subset of these individuals survived until the next year ("survivors").
The average of A is ...
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Is the term "joint model" only used in survival analysis?
I am used to seeing a joint model in reference to a combined longitudinal/survival model having shared random effects:
$$y_i(t) = \beta_0 + \beta_1 t + b_i + \epsilon_i(t)$$ $$h_i(t) = h_0(t) \exp\{\...
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