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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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Survival Analysis: event & censor coding

Simple query I suspect. I've been running a cox regression in R and noticed that my time-to event and time-to-censoring models produce identical output. Is that what I should expect? That is, does it ...
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Can left-censored data be normal distributed?

Very often I read that the distribution of IQ-test results is normal. However, the IQ-scale is left-censored, i.e. test results cannot be lower than zero. The normal distribution, however, is usually ...
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Tobit versus OLS, is dependent variable censored?

I would like to investigate possible relationships between arbitrage profit of crypto exchanges and exchange's order book characteristics, such as volatility, spread, liquidity. I compute the ...
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Effect of continuous variable with many repeated values on Random Forest

I am trying to build a random forest regression model in R using all continuous panel data. There is a large amount of data relative to the number of predictors. Say 500,000 rows and about 40 ...
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Compare samples with noisy data and maximums

Summary: I collected psychophysical data (i.e. yes/no responses to physical stimuli) testing the ability to feel a touch stimuli. I used a Bayesian algorithm to select the stimuli (30 trials per ...
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Missing Data for Binary Dependent Variable

I have a Binary dependent variable (0/1) with panel data of three years(1 2 3). I want to measure the determinants of a woman choosing abortion using ordinary probit or logit. The problem is that no ...
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Real 1 dimensional non-binary data where Cox Proportional hazards model fails

I am learning about the Cox Proportional Hazards model and understood that it is very flexible, even when the assumption of proportional hazards is not met, e.g. for additive hazards. But say we have ...
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multivariate truncated survival analysis

I have many short time series (1-5 data points) that document the development of morphological traits (length and pigmentation) of some lab critters in response to different dietary supplement. I ...
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Calculate E[X] from incomplete data?

The exercise I'm doing describes the random variable $X$ as the following ...
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Are cancer studies cases always left-censored?

I'm used to traditionnal studies with plain old Cox PH models and right censoring. But lately I was wondering about the outcome date in cancer studies. Indeed, the date we usually use as outcome ...
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5-year EFS > 5-year OS

I had a data of 24 cancer patients; their 5-year overall survival (i.e. event as death) was around 57%, however, when I calculated 5-year event-free survival for the same cohort, defining the event as ...
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Equivalence of Kaplan-Meier estimator and EM algorithm

For right-censored failure time data, in a non-parametric setting, is there an equivalence between using the EM algorithm (i.e. calculating the expected log-likelihood and maximizing) and the Kaplan-...
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Non-Informative Censoring for Non-Parametric Models

Under the assumption of a parametric failure time distribution and parametric censoring time distribution, the non-informative censoring assumption implies that the distributions share no parameters ...
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Survival Analysis - Account for heterogeneous time of entry with administrative censoring at year=T

I am new to survival analysis, although in the past weeks I have done my share of reading, hence this might be a non-problem. I have marriage and divorce data, spanning many years. I'm trying to model ...
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Exclude observations with measurements below limit of detection?

I am analysing a dataset for the relationship between an exposure variable x and a response y (in my case, these are urinary ...
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1answer
39 views

First passage time distribution via Monte Carlo simulation

The problem: I want to assess the first passage time distribution via Monte Carlo Simulation, where the first passage time is defined as: $$\tau=\inf\left\{t: X_t > l\right\}$$ where $l$ is the ...
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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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1answer
63 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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1answer
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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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1answer
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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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1answer
29 views

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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1answer
46 views

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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1answer
158 views

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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1answer
39 views

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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101 views

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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1answer
59 views

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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22 views

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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1answer
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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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47 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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1answer
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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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1answer
232 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 ...