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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Handling a censored factor score?

I have an 11 item measure for which I am computing factor scores. It is a censored (floor effect) measure. EFA/CFA analysis indicates I should remove 3 of those items. Whether or not I remove those ...
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32 views

Should one use a censored survival model when an event is only observed at death?

A colleague of mine is trying to estimate how neutron radiation exposure changes cancer incidence rates (in mice). He has autopsy data that reports whether a cancer was observed at the time of death, ...
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4 views

WinBUGS - sample from the posterior of exponential distributed survival times

as introduction to WinBUGS, I want to simulate the posterior of the Gamma-Exp-Model. Because the posterior is known, I can varify the result. But the true posterior is always shifted to the right. I ...
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21 views

Handling Informative Censoring in Survival Analysis

In a survival study with informative censoring (for example, studying the effects of cigarettes on mortality and smokers are more likely to be Lost to Follow Up). This causes the censored data to be ...
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24 views

Kernel density estimation with censored data

I have several univariate data sets that I would like to fit with a Kernel density estimator. However, some of the data sets contain left, interval, and right censored observations. How can I ...
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48 views

How to estimate mean and variance of censored normal?

Supposing I have data which I know is normally distributed, but because the recording process is right censored, how do I estimate the parameters of the distribution?
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1answer
28 views

Censoring “Death” in Time-To-Recovery Analysis

I am performing time-to-recovery analysis comparing 2 groups. In both groups, a few subjects died from the disease under consideration (instead of recovering). Is it appropriate to consider the deaths ...
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0answers
65 views

How to simulate informative censoring in a Cox PH model?

I wish to simulate events from a Cox PH model where the censoring is informative, and to compare parameter estimator quality with estimates obtained from data generated by a Cox PH model with ...
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30 views

simulate censored data (right censored) using R statistics [duplicate]

I want to generate right censored data, but I want to be able to pass in a parameter to a function to dictate that a certain percentage of the data will be censored. I have found this R-package: ...
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2answers
51 views

Survival regression variance estimates

I would like help understanding why a survival regression with no censored data-points does not give the same variance estimates as a linear model (see code below). I think it must be something to do ...
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26 views

Heteroscedastic censored regression

I am dealing with a heteroscedastic censored dataset. I tried to use the survival analysis package in R to estimate a linear model for it. So before doing that, I conducted a simulation study, where I ...
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14 views

Some details in Cragg's Limited Dependent Variable article

1) Is there anybody who can explain me the precise meaning of the indices and hence, dimensions of the involved matrices of Cragg's equation (18) in his Limited Dependent Variables article from 1971? ...
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1answer
19 views

Cutoffs to consider for survival tree

In an tree based algorithm a criterion is measured at certain cutoffs for the variable. This cutoffs are the candidate split points for that variable. How does one come up with candidate split points ...
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1answer
30 views

Left-censoring , $Y_i=\text{max}(T_i,U_i)$

In the book , Statistical Models and Methods for Lifetime Data , in Left-censoring , it is written that Can only observe $Y_i=\text{max}(T_i,U_i)$ . Where , ...
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27 views

Censored logistic regression

I have the following problem: We have data with a 0-1 outcome which can occur precisely once. It can occur at any time within a certain time period (say 3 years). For this data set, for some ...
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39 views

Question on Tobit Regression

Does Tobit regression assume that the dependent variable is continuous above the lower bound? I am trying to model mortality (ie. "dead" or "living" but not the time) based on a set of independent ...
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1answer
93 views

Method for fitting censored data in R

I have 320 data points - each has a redshift and a turnover-frequency, and I want to fit a correlation between them (a linear fit). However, 120 of the turnover-frequency values are upper limits. As ...
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1answer
39 views

How do you compare two “survival times” when there is no censoring per se?

I've gone through the 70+ questions when using "survival no censoring" as my search criteria, but I can't seem to find an answer to this very simple situation. I have patients' length of stay in a ...
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1answer
82 views

Python Astronomy Censored Data in Lifelines

I am trying to find a correlation between a given data set containing redshifts and turnover frequencies (I have a list of 320 galaxies, and the redshift and turnover frequency (a turnover frequency ...
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1answer
55 views

Survival estimation when death/censoring is probabilistic

I am trying to estimate survival function, but in case where each event is censoring with probability $p_i$. (That is, I am never sure if the event is right-censoring or death, but I can estimate the ...
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29 views

The most general definition of the Likelihood function for continuous data (including truncation and censoring)

How would you rigorously define the likelihood function for censored/truncated observations? Even in most lifetime/reliability literature (where these types of observations are frequently encountered) ...
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2answers
2k views

What is the difference between censoring and truncation?

In the book Statistical Models and Methods for Lifetime Data , it is written : Censoring: When an observation is incomplete due to some random cause. Truncation: When the incomplete nature of ...
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3answers
322 views

Right censoring and Left censoring

Wikipedia gives the following definitions: Right censoring: a data point is above a certain value but it is unknown by how much. Left censoring: a data point is below a certain value but it is ...
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13 views

Imposing follow-up time cutoffs on censored data for cox regression

When fitting cox regression models, is it valid to impose a cutoff for censored samples to have been followed for at least a given stretch of time for inclusion in the analysis?
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1answer
68 views

What model fit / predictive accuracy measure can be used to cross validate a Cox PH model with censored data?

How would you go about validating a Cox PH model with censored data? I am trying to run a Cox PH model on a dataset with observations that failed, and observations that are censored. Normally, I use ...
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15 views

Correlation of scores, when most scores are the highest

Let's say we have 10,000 observations of two kinds of scores for each item, i.e. each observation has two scores reported. The scores are from 0 to 100. Within each kind of score 9,900 observations ...
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2answers
233 views

How should I model a continuous dependent variable in the $[0, \infty]$ range?

I have a dependent variable that can range from 0 to infinity, with 0s actually being correct observations. I understand censoring and Tobit models only apply when the actual value of $Y$ is partially ...
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10 views

Examples of random censoring where it is unknown if there was censoring or an event

I am wondering if there are any (standard) examples of random censoring where it is unknown if there was censoring or an event occurred. To be specific say the time to event is the random variable ...
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1answer
321 views

Determining sample size for proportional hazard

I am in the design phase for a longitudinal study examining the effect of a predictor (neighborhood risk score) on time to an outcome (re-arrest), as well as whether or not the variation explained by ...
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14 views

Multinomial Heckman Models

I'm interested in modeling left censored data with a tobit model using R. Mine is a two step, as I want to generally predict probablity, and then quantity, so I'm planning on using a heckman. The ...
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1answer
51 views

Parametric distribution for time to event data - where event is 'uncertain'

Is there a canonical approach to deal with the modeling of time to event ($A$) where $P(A) \ne 1$. For instance, assume the marriage rate is 50%. The study is a set of times (ages) until marriage ...
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1answer
46 views

Interpreting tobit coefficients of 0

I'm using a tobit model for a left censored dataset in R, and including both continuous and categorical predictor variables. I've converted the factors to indicator coding for each level. I was ...
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0answers
17 views

estimate the pdf from mutually censored (competing) observations

Imagine we have three independent random variables, distributed according to pdfs $a(t), b(t), c(t)$, with cdfs $A(t), B(t), C(t)$. In my case the distributions are lognormal. However, our ...
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19 views

Inferences about a distribution given running maximum values

Here is a question inspired by this question from StackOverflow. Suppose you have observations of a variable which is measured once a minute, but the values are only recorded if they are greater than ...
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1answer
52 views

Person-time still contributed after censorship? (Stata)

I feel like I might be going a little crazy here, so I'd appreciate some advice. I have a multiple-record-per-subject dataset that goes something like this: id | day | failure ----+------+-------- ...
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40 views

Clarify terminology regarding truncated and censored distributions [duplicate]

I'm looking for clarification on the definition of truncated distributions and on terminology for censored distributions and truncated distributions. I recently had a [dialog on SO][1] regarding [a ...
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1answer
98 views

What is “Targeted Maximum Likelihood Expectation”?

I'm trying to understand some papers by Mark van der Laan. He's a theoretical statistician at Berkeley working on problems overlap significantly with machine learning. One problem for me (besides ...
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1answer
319 views

ML estimate of exponential distribution (with censored data)

In Survival Analysis, you assume the survival time of a r.v. $X_i$ to be exponentially distributed. Considering now that I have $x_1,\dots,x_n$ "outcomes" of i.i.d r.v.'s $X_i$. Only some proportion ...
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1answer
20 views

Max fraction of censored values for Cox regression?

I'm not sure whether there's an exact answer to this, but I'm wondering in the simplest case of doing Cox Regression with censoring on one variable, if we have N measurement values, what number (k) of ...
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99 views

fitting a model for time series data

Folks, I am working on time series traffic data where the waiting times are indexed over time, with 288 observations for 24 hour time period (interval of 5 minutes). I am trying to cleanse the data, ...
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49 views

Evaluating survival models in the presence of covariate-dependent censoring

I have a censored survival analysis problem with the following characteristics: Failure times are discretized The censorship distribution depends on certain covariates I don't have a ...
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0answers
29 views

Incomplete inhibition curve fitting with Graphpad Prism6

One of my data set shows incomplete inhibition (for high concentrations points, inhibition response goes up to 45%-50% (of control). I am fitting my data using log(inhibitor) vs response -Variable ...
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129 views

Censored data from a truncated distribution (Stan)

I'm trying to write a survival model of fossil species durations. In this case, the minimal possible duration for a species is 1. Also, the general idea in paleontology is that we are only observing a ...
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26 views

Expectation maximisation for right-censored iid data from Normal

This is the data (which are length of ropes), $\textrm{Data}=\{99, 70, o ,89, 88, o, 88,70, o ,o\}$, where $o$ are censored data with value above $100$. Assume that data are from $\textrm{iid} \sim ...
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1answer
454 views

Tobit versus OLS

There is a dependent variable which is measured in £ and can take the form of £0-£100,000. It is effectively the value of the payment made. If it takes the form of £0 it means a payment was not made ...
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465 views

What exactly are censored data?

I have read different descriptions of censored data: A) As explained in this thread, unquantified data below or above a certain threshold is censored. Unquantified means data is above or below a ...
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57 views

Run Tobit with missing values (from linear prediction) or change them to zeros - STATA “practical” question

I want to run a Tobit linear regression in order to especify a labor-supply curve (linear-linear). As dependent variables I have personal characteristics, enviromental ones, and wages (predicted using ...
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67 views

Error using “cengaussian” family with MCMCglmm

I'm trying to run a model using a cengaussian family distribution with the function MCMCglmm. The model is: ...
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76 views

Using standard machine learning tools on left-censored data

I'm developing a forecasting application whose purpose is to allow an importer to forecast demand for its products from its customer network of distributors. Sales figures are a pretty good proxy for ...
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2answers
503 views

Mean value of truncated normal distribution

I have a bunch of data where each observation represents an error $\in [0,1]$ (computed error between a variable and it's ground truth). Extra info: These are the results of the difference between a ...