Questions tagged [censoring]

The process of censoring yields data w/ only partial information. The most common example of censoring is *right censoring* in survival analysis, where the time until the event occurred is only known to be longer than some duration because the event had not occurred when the study ended.

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42 views

Cox Regression - Censoring data (R) [closed]

Summarizing my questions: Do I need to load the data in a special way(details on my data below)? When I see the event at time (t) is that time from hire, or time from the day the data was pulled? At ...
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36 views

Survival Analysis - Right Censoring Data

I am using Survival Analysis to build an attrition model. I have a data set with ~15,000 people that spans the past 5 years. Approx. 2,000 left in the last 5 years. The remaining people stayed at the ...
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28 views

Sampling censored empirical distribution

I have a dataset with lifetime values that is right-censored. My goal is to estimate the lifetimes of all items in the set that are censored. Here is what I did so far: Use Kaplan-Meier to build the ...
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Estimating long-term side effects of anti-covid vaccines in short time (statistical design of clinical trials)

I am interested in statistical procedures and study designs used to determine the absence/acceptability of long-term sude effects of the anti-covid vaccines. Given that these vaccines were created and ...
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Bootstrapping to address interval censored data

I am trying to run a cox proportional hazards model on data that is interval-censored (and I guess right censored). Within this model, I believe one of my covariates' relationship should be modeled ...
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Misconception about left censoring

While trying to learn about censoring, I stumbled across a sentence on Wikipedia which I do not understand: A common misconception with time interval data is to class as left censored intervals where ...
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39 views

Transforming a right-skewed continuous response variable to an ordinal one: is this dumb?

I am estimating task time-to-completion using a sample size of ~36k. ~34k points are complete, ~2k are not. The response variable for my sample is right-skewed. I want to use this data to predict how ...
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Right censoring treatments: complete case, MICE and IPW <Pros and Cons>

I have always been a bit unsure about how to deal with right-censored data. From my experience, most clinical researchers around me prefer to use complete case analysis to treat right-censored data, ...
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Test if a sample comes from a theoretical distribution (with a specific type of censoring)

My situation is the following. I am estimating certain numbers from a dataset split in $n$ parts, one number for each part. How and why exactly is not relevant to the current question, but as a toy ...
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Question about the effect of administrative censoring time point on survival analysis

Imagine a simple Kaplan-Meier analysis where administrative censoring is applied at time=5 years. In other words, I may have follow-up data on persons out further but i am choosing to censor them at 5 ...
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Hall and Wellner survival function simultaneous confidence band

I was trying to implement the Hall and Wellner simultaneous confidence band decribed in: Applied Survival Analysis, Second Edition (ISBN-13: 978-0471754992), p. 33. But the table (Appedix 3) requires ...
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Truncating variable in survival analysis

this is my first time developing a survival analysis model so bare with me if the nomenclature is not on point. Basically, I'm running a Cox PH model for the length a contract is active, where 1 is ...
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Does censoring exist when actual outcome is known for every subject at end of study?

Suppose I have a "study" that occurs each year. Subjects can enter the study at any point in a given year (although most enter at the very beginning), and once they're in the study, we ...
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Random Censoring scheme in Weibull Distribution

I'm trying to derive the estimators of the parameters using maximum likelihood method for Weibull distribution in random censoring scheme $f(t)=\alpha\lambda(\lambda t)^{\alpha -1}e^{{-\lambda t}^{\...
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42 views

Explanation of posterior distribution under censoring

The question is a 2 parter. I am trying to model some data that is left censored (not time to event data) and for clarity I want to do it the same way as in the BDA3 book example here: Question #1: ...
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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 analyze data where one levels of treatment is left censored and other levels of the treatment are right censored?

I have data from an experiment where we looked at the time-to-death of pseudoscorpions under three treatment conditions: control, heat, and submersion underwater. Both the control and heat groups were ...
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Forecasting surface visibility with (right-)censored data

I have a bunch of surface visibility data measured at several ground weather stations over a certain period of time. The data for some of the stations are right-censored, e.g. a significant percentage ...
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Is treating discharged patients as censored ok when using a cox proportional hazard model?

When analyzing the association of in-hospital death (the event) with various independent variables using a cox proportional hazard model, is it acceptable to treat as censored both: (i) the patients ...
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Understanding censored likelihoods

I'm a little confused about how to interpret the maximum likelihood procedure for censored data. I'll write out an example, and then ask my question -- it's sort of a soft question, so my apologies if ...
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GEEGLM or NEGBIN with offset person time follow-up

I am analyzing number of hospitalizations in 5 years of followup for a cohort of subjects. Some of these withdraw before the end of study. How can I consider it in a model for count data? Is it ...
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Modelling an output with mixed continuous and discrete values

Some variables that we may be interested in modelling, can take both discrete and continuous values. For example, let's say we want to model the time until the next customer arrives in our shop on a ...
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1answer
27 views

Estimating survival functions for interval censored data

I have a longitudinal dataset of about 350,000 individuals who had diagnostic measurements taken within a specific time period. The number of measurements per individual varies and the measurement ...
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How to deal with overlay censored reliability or survival analysis (over 95% of the data would be censored)?

I have data for Engineering structures that are built sometime after 1900 until recent years. The inspection data for these structures are available from the 1980s onward until now. The inspection ...
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How best to deal with a left-censored predictor (because of detection limits) in a linear model?

Context: I'm new to Bayesian stats and am trying to fit a multiple regression with rstan. All variables are continuous and there is no hierarchical structure. One ...
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Censored multinomial with different, observed censorship pools

In the problem I'm working on, I'm trying to infer the proportions of three types of object $A, B, C$ in a population. I'll use $p_A$, $p_B$, and $p_C$ to refer to the proportions. The data I get to ...
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What is (are) scenerios and practical settings that can possibly lead to the weibull-log-Logistic mixture distribution?

In my paper I studied Weibull-loglogistic mixture distributions in reliability and life testing, some structural properties of the model are presented including moments, reliability, hazard rate ...
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Is it Sufficient to Truncate a Left Censored Distribution?

A colleague explained their approach to dealing with left censored data in an analysis, and while I don't think it is the best approach, I am not sure if it is insufficient or not. My colleague has ...
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45 views

C-Index for few failure cases

I'm training a Cox model on top of a CNN to predict the overall survival of head and neck cancer patients based on CT images. In order to rate the models performance I'm using Harrel's C-Index. To get ...
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Can one make meaningful predictions from “censored data”?

In an ML project, I'm using patients' clinical and demographic features to predict their treatment outcomes. Among over 300K records, only 6,022 are known to have experienced severe conditions (ICU, ...
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What does the detection limit indicate?

Say I have a data set of 6 samples that give me the concentration per mL for each sample. Data: 5 g/ml 7 g/ml 3 g/ml 4 g/ml 5 g/ml 6 g/ml Here the standard deviation is 1.414. The critical value for ...
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Analyzing cost of treatment in a cohort (varying follow up/available data) at multiple time points

I would like to look at total cost of treatment from an index date (treatment initiation) after 1 month, 3 month, and 6 months. However, my data has has issues where patients drop out at varying time ...
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Survival analysis with unobserved right censoring

Assume we have a tire shop and would like to build a survival curve for the lifetime of our tires.Once we know how long our tires are useful, we can send push notifications prompting customers to get ...
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Kaplan-Meier IPCW

My dataset is composed of n individuals (patients) with a two-year follow-up at maximum. Every patient is sane at the beginning of the study, and each month we note if the patients got a certain ...
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Meaning of “Cox model censoring at relapse” in simple words

I'm translating into Russian a news report on the results of a clinical trial: Quote: Bruce Cree, MD, PhD, MAS, lead author, and neurologist, UCSF Multiple Sclerosis Center, and colleagues found that ...
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Can I conduct Kolmogorov-Smirnov test on censored data?

Normally, Kolmogorov-Smirnov is conducted on full, uncensored data with test statistics. $$ sup_x |F(x)-F^*(x)| $$ Or equivalently, $$ sup_x|S(x)-S^*(x)| $$ ,where $F(x)$,$S(x)$ is proposed ...
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Flip the sign of covariates in Cox model

I am just curious what will happen to beta (the coefficients) and its confidence interval when I flip the sign of the covariate (multiply all elements to -1) in Cox model for right censored data.
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Censored data - When does it matter

In survival analysis, one may arrive at a series of samples $X_1,...,X_n$, for which the outcome of a given $X$ may not be "observed" within the experiment. For instance, if the $X_i$'s are failure ...
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Cox model appropriate for my time to event problem?

I am trying to estimate the factors associated with delay in implementation of a policy. I am analyzing the delay, measured by number of days, it took an entity to implement one of three policies, ...
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Bound on Error from Censoring

Suppose I have $N$ Gaussian random variables $X_1,...,X_N$ where $X_i \sim \mathcal{N}(0,\sigma)$. Suppose I censor each $X_i$ to lie in the range $[-t,t]$. Denote the censored values by $Z_1,...,Z_N$....
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How to do a Cox regression with progressive type I censoring?

I'm working with a problem where I have a progressive type I censoring. A batch of rats is censored after 7 days and another batch is censored after 14 days (the study ends after 14 days). The event ...
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Distribution of censored data with Kaplan-Meier

I have a set of right censored data from a variable $T_{out}$ that expresses the survival time of a patient. In order to understand the distribution of this random variable, I used the Kaplan-Meier ...
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1answer
101 views

Generating censoring times for the cox proportional hazards model

I am trying to understand the different ways of simulating survival times in a cox proportional hazards model. A simple example consists in simulating the event times following a Weibull distribution. ...
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82 views

Survival analysis - dealing with highly censored data with computationally expensive covariates

I have approximately 1000 run-life examples (time to fail data) for equipment. However, the number of failures is quite low relative to the number of units that are censored (95% are right - censored, ...
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68 views

Maximum Likelihood Estimator for Censored Data

Let $X^n=(X_1,X_2,...,X_n)$ denote a sample where (1) $X_i=\mathbf 1_{(\epsilon_i + \mu \geq 0)}(\mu+\epsilon_i)+\mathbf 1_{(\epsilon_i + \mu \leq 1)}(\mu+\epsilon_i)+\mathbf 1_{(\epsilon_i + \mu &...
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Measuring the risk of an event among hospital patients in survival analysis: should you censor patients who do not have the event?

I am trying to plot the risk of self-discharge from hospital over time ('self-discharge' means leaving hospital against the wishes of your doctor). In my data, hospital patients have a duration of ...
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18 views

Left-censoring in Cox Model consequences

I would like to study the association between partner age at surgery and individual survival. I am doing a Cox model using as starting point of the risk individuals' age when the partner had surgery (...
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24 views

Survival Analysis with right-censoring

I have the following data, which represent the realizations of the variable T = min(Y, C). Some of the data is right-censored (+) ( 5.3, 12.1+, 11.7, 10+, 2.2, 9.8, 9.2, 3.5, 5.7+, 9.2, 3+ ) To ...
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Does the quoted line mean that the 6 cars would have gained more miles? If not, what does it mean?

I am reading Jayant Deshpande's "Life Time Data: Statistical Models and Methods" book and while reading about Right Random Censoring, I read about this example. Example of Random (right) Censoring ...
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Can you illustrate the following with the help of a graph?

Can you please help me visualise the following situation using a graph or anything? Also, where does the "life time" start from and where does it end? The data set may contain both left and right ...

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