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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What model do I use if I have two response variables which are influenced by each other?

I conducted an experiment where I looked at measuring animals performance for a certain task. I have 2 response variables 1.success/failure at performing the task (bionomial); and 2. latency (time) to ...
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29 views

Right censoring with recurrent events

I am dealing with retrospective survival data covering 60 years. Some people start their first spell in 1960, others start their first spell in 2000 (they are never left truncated). People can ...
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What regression approach would suit zero-inflated data that is censored at a fuzzy threshold?

Monthly grid-cell burned area estimates are (almost) lognormally distributed, censored at a fuzzy threshold and zero-inflated. I want to predict burned area from weather etc. About 40% of the ...
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Survival Analysis for Attrition Study and Informative Censoring

I am trying to develop a model to understand attrition among students. Apart from binary classification, I am thinking of performing a survival analysis by following the students for 3 years at the ...
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74 views

How can I fit a regression for a variable which have a maximum value?

Let's suppose I have a test which gives me the dosage of an analytic in the blood. The results of the assay are in a range of 0 and 1000; all subjects who have a value higher than 1000 will be ...
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29 views

Estimator of a censored exponential

I am trying to self-study the MIT OpenCourseware course on Statistics, here: https://ocw.mit.edu/courses/mathematics/18-650-statistics-for-applications-fall-2016/syllabus/ On problem set 4, question 3 ...
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Aggregating (taking the mean of) a censored variable

This post is related to this post. I have survey data, with a (censored) range from 0-100, that looks as follows: ...
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Can you have “missing” predictors in Cox regression or are these just considered [right] censored data?

If data is extracted from electronic health records and used for survival analysis, can outcome vars be considered missing or are they just considered right censored data points?
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Survival analysis to estimate kanban tasks completion times

I am working on a problem to estimate task completion time in kanban (project management tool). While doing EDA, I looked at tasks that are either done or cancelled. In this case, I defined the ...
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R: Left-censoring a probablity distribution function

I would like to left-censor (at zero) a probablity distribution function, but I just can't find a way to implement this in R. I have reviewed previous questions about censoring, but none have provided ...
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Modelling Task Completion Data

I have a two dimensional dataset - the first variable ($t$) represents time, and the second ($y$) is bounded between 0 and 1: Think of $y$ as percentage completion of a task. $y$ is dependent on $t$ -...
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Intuition behind Brier score weighing step for censored data

Sources seem to suggest that when calculating Brier scores involving right-censored data, one must weigh the otherwise mean square error function with the inverse probability of censoring weights ...
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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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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 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 side effects of covid vaccines. Given that these vaccines were created and approved ...
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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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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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34 views

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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29 views

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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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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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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361 views

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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52 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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132 views

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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39 views

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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