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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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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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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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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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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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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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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Constrained Nonparametric Density Estimation with Right Censoring

Is anyone aware if there is any available open source R (or other language) code which implements non-parametric estimation of the failure time density function subject to a monotonicity constraint on ...
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Validating censored labels

I have a database of $P$ patients' hospital encounters over a period of $T$ years. Patient $p \in \{1, 2, \ldots P\}$ visited the clinic $N_p$ times. If patient $p$ was diagnosed with condition C ($...
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Independence of censoring time $C$ and event time $T$ for randomised entry to a study

While reading through the textbook 'Modern Applied Statistics With S' by Venables and Ripley, I came across the following paragraph detailing the different types of censoring possible when dealing ...
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Example of informative and independent censoring

I was trying to come up with an example of informative and independent censoring which wouldn’t be completely unrealistic. The artificial example would be a study in which the censoring time of an ...
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Exposure onset unknown in time to event analyses

If I want to model the time to an event (cancer) in a group of patients exposed to e.g. a cancerous substance. I now have some people where I do not know if they were already exposed to the substance ...
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Why should the right-censored observation be excluded from demonimator in KM estimation

It is well acknowledged that we cannot extrapolate the lifespan T of the censored observation. In the Kaplan-Meier estimation, the estimated $s(t)$ for $t∈[t_j,t_{j+1}]$ is estimated using: I am ...
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How to interpret left and right censoring

I am fully aware that question regrading left and right censoring has been asked before. I will however post my own question, as I believe that its focus differs significantly. Here goes: I have a ...
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Stepwise regression for left-censored using NADA - R

I'm working with environmental data which are left-censored and I found the R package NADA which seems to do the job. After fitting a complete model, using the cenreg function,I'd like to do a ...
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Problems with informative censoring in survival analysis/failure time analysis

I recently began self-studying certain topics in survival analysis and just became acquainted with the concepts of 'informative' and 'non-informative' censoring. To illustrate the gaps in my current ...
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Using a logistic regression on censored data

I am interested in modeling the probability of default (PD) of a loan product. Data I have a dataset going back several years. Most of the loans have reached their terminal state (paid off or ...
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COVID-19: Do epidemiologists use censoring methods to calculate case fatality rates with undercount?

In case of the coronavirus COVID-19 (or 2019-nCoV), it seems that there are a lot of mild cases which do not require medical intervention, see here: For every person who is sick enough to come to ...
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What exactly is meant by bias in this context?

I'm working through an example of survival-time analysis with censored and un-censored data. We're given the survival times of 94 patients. Some of these survival times are censored i.e.in this ...
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How to impute right-censored data

I have a dataset of vectors representing movement with various characteristics. Some vectors represents the movement that was stopped by external factor and therefore, observed value for length of ...
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Manually predict lognormal survreg model considering parameters uncertainty

I'm analyzing environmental data using the "NADA" R library, which relies heavily on the "survival" package. I am dealing with left-censored data, which are nonetheless strictly positive. To deal with ...
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How to train a new classification model based on the labels obtained from the existing model? [duplicate]

We have a credit scoring model based on the logistic regression that we currently use in production. Every person who wants to get a short term loan is being scored by our current model and is either ...
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multivariate Cox proportional hazards

in my study we have a prospective cohort, and we collect several biological samples, say n different samples. Most of the samples are collected at recruitment except for 1 which is collected at ...
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A workaround for using linear models (rather than Tobit) with censored data?

I have a left censored dependent variable where many of the observations have a value of zero. The data is clustered (multiple measurements over time for each person). I initially decided to use a ...
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Truncation versus censoring with Kaplan-Meier

I am trying to run Kaplan-Meier on a rather odd dataset and am having difficulty determining whether I should be truncating or censoring my data. I have looked at the other feeds, including this very ...
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How to include out-of-limit measurements (such as negatives) in regressions

I am trying to compare two diagnostic measurement techniques using Deming regression. Both of these techniques have their own lower limits of detection, and my data include both numeric values as well ...
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Estimation of censored regression model

I am refreshing my knowledge with respect to econometric modelling in general. I came across page 201 of the book 'Enjoyable Econometrics by Philip Franses' and I had some difficulties interpreting ...
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How to fit a distribution with an “10 and more” category at the bottom?

I want to fit a distribution to some data to sample from it in a subsequent simulation. There are I got a dataset that looks somehwat like this: ...
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Multiple regression for left-censored independent and dependent variables

I am interested in developing a predictive multiple regression model which predicts a concentration of one compound based on the measured concentrations of several other compounds. Both the dependent ...
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Mixed Effects Model Using Censored Data

I am attempting to analyze left-censored hormone data collected in a repeated measures design, and am having some difficulty employing an appropriate method to account for the censored nature of the ...
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Is there a way to compute the Kaplan-Meier mean for left censored data using lifelines in python? [closed]

I am using the lifelines python package to fit Kaplan-Meirer models to left-censored environmental data. I am computing the mean using lifelines.utils.restricted_mean_survival_time(m,t) where m is ...
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Modeling entering a lifelong treatment at different ages

Let's say I'm working on a pill that extends (or reduces, if I'm a bad scientist) the life of anyone taking it. It only works on individuals at least 70 years old, but they may start taking the pill ...
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How to graph a survival function when time is one of the IVs?

I am reviewing an article, so I can't be too specific, but the authors are doing a survival analysis of outcomes of stroke and one of the independent variables is the time that the person had a stroke ...
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Unbiased estimation of regression coefficients conditional on a range of the dependent variable

I am interested in the relationship between a set of explanatory variables and a particular outcome variable for values of the outcome above a certain cutoff. Can I simply regress the outcome on the ...
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Null Target Variable

I am trying to predict - Number of days it takes for a customer to make the second purchase. Sometimes the customer comes back in 2,5,6,10.... days and sometimes the customer does not come back which ...
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“Double censored” model?

How would I properly model the following: A disease has three stages of diagnosis: No symptoms, Mild, Advanced. These are based on behavioral criteria. There are also brain pathology scales that do ...
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Appropriate censoring and truncation for customer survival analysis

I am working on a regular customer survival analysis problem. Here I analyze customers who signed up between 2015-1-1 & 2018-1-1. Customers can register anytime during this interval and exit ...
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Comparing empirical and theoretical estimates of the number of right-censored values

Suppose I have right-censored data, so that observations are still present but are top-coded. In my case this is income data for, let’s say, individual people, and associated & probability weights....
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variance estimator for a symmetrical two-sides censored normal distribution

Suppose to draw a sample of $n$ observations from $X \sim \mathcal{N}(0,\sigma)$, with observations outside the interval $(-c,+c)$ censored; $c$ is known and one can conveniently set $c=1$, for ...
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Marginal log likelihood for Tobit model heteroskedasticity link function

I am using a Tobit estimator for a demand model left censored at 0. To account for heteroskedasticity, I specify the standard error as follows (using the crch function in the R package crch): $log(\...
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Right truncation and right censoring

Is is possible for a survival data to be **right truncated and right censored **. If so, please leave an example for better understanding. Thanks in advance!
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Variance-covariance matrix of multivariate response, with censored values: MCMCglmm alternatives?

I have a dataset I need to analyze in which I'm interested in the relationships among several variables, after accounting for covariates that may affect some of those variables. More specifically, I ...

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