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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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Using survival analysis in hockey analytics- Period 1 vs Period 2 as Treatment variable

In my article on hockey analytics, I answer how different are the rates of goals, shots, or hits from the NHL regular season to the playoffs (Playoffs are games played by the top 16 teams in the ...
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Simulation censored data in R

I am trying to simulate a data set of interval censored data(finite interval censored data, right censored data ,and left censored data). In fact, I created two monitoring times in R and I have the ...
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How to deal with the problem of censoring in tree-based machine learning?

Censoring occurs when the outcome of a unit is not observed, because the unit is lost to follow up in a longitudinal study. Let $Y_t$ be the survival time at $t$. Then a unit is censored at $t'$ if $...
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Right Censored Sales Data

Suppose I want to estimate the true demand D for product X. Where D = sales if the inventory > 0, and D = right censored from observations of sales if inventory = 0. Suppose I have the following data,...
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A survival (accelerated failure time) regression model for censored data across several trials

I have this experimental design: Two groups A and B. Individuals from group B were genetically manipulated such that when they are given a certain drug the drug turns on a gene that was inserted ...
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60 views

Inverting data for Zero-inflated mixed effects models

I am looking for some advice on my analyses, I have been going back and forth between co-authors about the validity of my approach and would appreciate some external input. My data are derived from ...
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Censored Regression/Tobit: coefficients decrease drastically when non-normal distribution is assumed

I am trying to use a Tobit/ censored regression model to estimate the effect of a certain political condition on a tax. Our dependent variable is zero-inflated because in most of our observations this ...
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25 views

How do we maximise power for observational proportional hazards model?

This question relates to the optimal study design when looking at survival to event based on observational data (i.e. the precise time of event will be unobserved but we can observe status at times ...
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In survival analysis, how do you deal with different amount of censored data affecting the endpoint of hazard curve?

I am working on determining the lifetime and reliability of a component using survival curves. I am stuck on how to compare the different curves when they have different endpoints. The curves are log-...
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How can we predict reliability for type 1 censored data?

I am working on a somewhat challenging problem. I have data for a large set of equipment. My main research question is: How many units will fail in each future month in the coming decade? So far I ...
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In survival analysis, is all censored data weighted the same?

I am working on a survival analysis problem and I am having trouble wrapping my head around the weighting on right censored data. If I have a group of right censored data where the time is longer ...
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regression approach for missing data (left censoring?)

I have a regression problem where I want to predict actuals (dependent variable) of some process where I only have values for a small number of independent variables at the beginning of the process ...
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censored regression problem if dependent variable only above threshold?

I have to predict some continuous dependent variable of samples where the value of this continuous dependent variable is only above a certain threshold (i.e. predict large values). Does this ...
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Likelihood Construction for Censored Data

I am trying to understand the Expectation-Maximization algorithm, and was trying to read through this paper by Park and Lee. In section 2, "Likelihood Construction for Censored Data", they mention the ...
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Competing Risk Regression, events at same timepoint

I have multiple timepoints for Events like stroke, death, reoperation. I want to use competing Risk Regression for e.g. death and reoperation. While censoring, I realize, that aswell death and ...
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Censored regression with right censored data

I'm kind of new to Stats and R in general and I'm looking to clear some doubts. I'm trying to use Censored regression models to do the analysis of my qPCR data. The response variable is continuous (Ct ...
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Tobit model: Left and right censoring

In my data, my outcome variable days.to.event is conceptually left censored at 0 days and right censored at 30 days. However, since the ...
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Tobit model with flexible censoring point in R

I am currently writing my MSc thesis and I am using a Tobit model. My data consists of fleet and sales data. The censored dependent variable is quantity and this quantity is higher than the fleet ...
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Piecewise integration

I am trying to estimate residential demand for electricity in a country where electricity is sold (to all households (HH)) at an increasing two-part tariff. By choosing marginal prices as my key ...
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Is data censored if it's “still alive”?

Let's say I'm observing the mortality of flies. Say I have 100 flies that are born throughout the year. And also say I am recording the alive/dead status of a fly every single day, without fail. So ...
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How does the tobit model relate to parametric survival model?

Is the Tobit model equivalent to a log-normal parametric survival model? If not, what are the pros and cons of a log-normal parametric survival model over a Tobit model?
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Mean of a censored Poisson random variable

Consider a real demand estimation problem of a retailer where matrix $Y$ (contains Poisson random variables) is the real demand and its mean need to be estimated by using sales data (matrix) $X$ which ...
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Help with Right Censoring for survival analysis

Hi all I would like to do some survival analysis. The most difficult part for me is setting up the censoring data correctly and I would appreciated if someone can help confirm if I'm doing this ...
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Estimator of (left-)censored normal distribution when mean>>std

Suppose there is a left-censored normal distribution, and we know there is a total of $m$ samples, for which we know $n$ of them. I am trying to estimate the mean and variance of the underlying normal ...
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What is the distribution of min{0,X} when X follows some general normal distribution?

What is the distribution of $\min\{0, X\}$ when $X$ follows some general normal distribution?
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R: icenReg: How do I fit a Bayesian model without any groups?

I've encountered a rather strange problem with the icenReg package. I'm trying to fit a Bayesian model to some interval-censored data. I'll illustrate this using ...
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R: “survival” package seems to underestimate survival times for interval-censored data

I'm trying to analyse some survival data. I have a collection of "time-to-failure" measurements that are interval censored: the failure time $T$ is not measured directly, but is known to have taken ...
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R: Problems using the “coarseDataTools” package for interval-censored data; optimization fails

Background information: In data from a disease outbreak we may want to estimate the distribution of the incubation period. However, we often don't observe the exact time an infection occurred, nor ...
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Linear regression: how to treat an explanatory variable that is discrete but does not have a natural zero

Background/study system: One of my MS students is studying the biomechanics of strand breakage in Spanish moss (an epiphyte--or plant that lives on other plants). Spanish moss has strands that can ...
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Can the vanilla Aalen's regression method handle both right censored and left censored data?

I know that vanilla Aalen's regression method can be regarded as an extended version of the Cox survival regression. I read that Cox regression can handle right-censored data but NOT left-censored ...
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Calculating censoring proportion in recurrent event time data

My question pertains to how to calculate censoring proportion in the perspective of recurrent event data in which an individual subject can have multiple survival times related to repeated occurrences ...
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36 views

Survival model - sample with only censored observations

I have a question related to survival models: for instance, the survival probability of people that have a disease. In all examples I've seen so far, the data used to estimate those models sometimes ...
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survival analysis with varying follow-up time

I have a retrospectively enrolled cohort of patients with aortic disease. The endpoint is aortic enlargement at or after postoperative 6 months. Patients experiencing aortic enlargement within 6 ...
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Estimate the conditional probability given contaminated output?

I have a dataset with exam grades and for each student an indicator variable that is equal to $y=1$ if the student was cribbing and $y=0$ otherwise. As a result of the crib the grade is expected to be ...
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163 views

Fitting distributions on censored data

My question deals with fitting distributions on censored data; for the purposes of clarity, we can consider a continuous distribution which is both left and right-censored. In such a case, the ...
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How to fit a (gaussian) mixture model to a dataset with (right) censored data in R?

I am trying to fit a mixture distribution to a dataset in R. Exploiting the R package mixtools, this goes pretty well. However, up to 20% of the data point in the dataset are right censored, therefore ...
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survival analysis: right censored data as test data

I have a survival analysis use case where the data which would be right censored is also the data I am looking to make predictions on. So the training data's censored observations would also be the ...
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OLS with shares as outcome

I have a regression where my outcome are share measures within a household (share of underweight for example) and am pondering whether this is a case of censored regression? My intuition is to think ...
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177 views

Anyone familiar with Tobit panel models w/ random effects (and Stata's xttobit and metobit)?

I am not an expert when it comes to econometrics but I find myself in need of carrying out an empirical analysis. My question pertains to how exactly I might (or should) go about specifying the random ...
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Censored regression methods for analyzing extreme end of a normally-distributed variable

I have a normally distributed continuous variable referring to an observed human behavior, and I'm interested in measuring or rather analyzing the extreme of this behavior, namely, the top 10% of the ...
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Crossed random effects with censored response?

Is there some way to do regression on a computer (preferably in R, but I'm willing to try out other software as long as it's something I can find access to) with a censored response and crossed random ...
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Suggested method for data with assumed non-proportional hazards

We are planning a study on longitudinal healtcare data. Exposure is starting a certain medication ("A"). Controls are those in the dataset not starting A, matched on age, sex and some other variables. ...
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Time to event with continuous value attached to event

The data would have three basic outcomes: No sale. Sale with dollar amount. Still in process. I would have potential predictors to test. There is a time component, as well. If the data were no-sale/...
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Which duration model to use with a fully right censored database

Currently I'm examining the duration of residence of households. I have a database at my disposal that indicates how long a specific household resides in its current home. I want to explain their ...
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57 views

Logistic regression with double censored independent variable

I want to do logistic regression using a antibody titer (continuous independent variable) and protection status (binary dependent variable). The antibody titer are not straight away continuous ...
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135 views

How to model left-censored and right-truncated data on Stata? [closed]

I have data that is left-censored and right-truncated. I'd like to run a tobit or truncreg. Although, using ...
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1answer
90 views

Residual Useful Life estimation from multivariate time series with lots of missing data and censoring, using neural networks

I have a set of industrial machines, for which I collect measurements from a few sensors (say, $d=20$) in time. So I have a $d-$variate time series for each machine. Let $t=0$ denote the start of my ...
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How can we deal with limit of detection independent variables in regression

Suppose that you have a regression in which one or more of the independent variables has a lower limit of detection (e.g. some result of blood tests). How best to deal with this? Any pointers to the ...
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Proper way to assess median failure distance in the presence of censoring

I would like to measure the median distance at which a material fails when it is stretched. At first pass, this sounds trivial and there is a simple version of this by which I pull a material until ...
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1answer
155 views

How do left-censored data and right-censored data impact Cox Regression?

My application is not a traditional survival analysis scenario. However, I believe survival analysis methods, e.g., Cox regression, can be a possible solution. In particular, my dataset contains two ...