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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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58 views

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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19 views

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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34 views

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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30 views

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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1answer
84 views

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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15 views

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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29 views

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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22 views

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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16 views

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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14 views

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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14 views

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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1answer
21 views

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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13 views

“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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17 views

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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15 views

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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24 views

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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25 views

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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32 views

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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34 views

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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1answer
55 views

How to find the mean lifetime of right-censored data?

Suppose I have a group of patients (the following are their lifetime, * means this individual is censored): 30,67,79*,82*,95,148,170,171,176,193,200,221,243,261,262,263,399,414,446,446*,464,777 The ...
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31 views

EM algorithm for lognormal with time right censored data

Is there any literature out there that discusses this problem mentioned? I know that it is apparent in survival analysis but I could not find any resources relating to this topic EDIT: using the EM ...
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49 views

How to manually calculate the standard errors of autoregressive terms and sigma in regression equation?

I have fitted a censored regression model in R which whose outputs look like this ...
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1answer
81 views

Hurdle model vs left censored model

When dealing with response variables that have lots and lots of zeros, is there a clear argument for when hurdle models are preferred and when left censored or tobit models are preferred?
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27 views

Multidimensional scaling with censored and missing distances

I would like to apply MDS to a high-dimensional distance matrix but the difficulty is than the distance matrix contains many missing and censored values (i.e. distances like >8). Does anyone know of ...
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38 views

Censored regression but dependent variable is sum of two censored variables

Suppose we have two censored variables: $$y_1 = \begin{cases} 0, & y_1^*\leq 0\\ y_1^*, & 0< y_1^* < 1000 \\ 1000, & 1000<y_1^* \end{cases}. $$ $$y_2 = \...
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44 views

GLM modelling for censored data

I am doing a model on average claim cost. My dataset has the cost data right censored at different limits (10K, 20K and 30K). My goal is to determine the unlimited claim cost from this data. I was ...
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1answer
43 views

Picking from Logistic vs Survival Model

I have a health data set for measuring the effectiveness of a drug. (Age, Gender(0,1), Morbidity(1,2,3), Dosage(0,1), Group (a,b), Effect (Not effective =0, effective = 1), and Time (days needed for ...
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42 views

Right censored or right truncation and Cox model?

Suppose, a list of targeted population is invited to participate in a health program. Invitation date could vary for every individual based on eligible criteria (this criterion is the same for all). ...
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21 views

Modeling count data (left skewed, underdispersed, right-censored)

I am seeking to model a count response variable-- number of times subject enacted a compensatory behavioral strategy-- as a function of cognitive and behavioral symptomatology, which are both ...
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19 views

Survival analysis with quarterly data: Is it really interval-censored?

I'm looking at data where all of the measurements are only available with quarterly time points, e.g. 2005-Q1, 2005-Q2, ..., 2016-Q4, 2017-Q1. This means that the event-of-interest (e.g. death) falls ...
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39 views

Using log data with censored Poisson regression

I am trying to minimise a likelihood function and estimate the parameter value of $\lambda$ by fitting to the following data. $t$ is the time and $N(t)$ is the population measured at those specific ...
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1answer
42 views

Censoring linearly splined predictor in regression

I'm developing a logistic regression where one of the independent variables has a non-linear relationship to the probability of the event occurring. I have created linear splines based on this ...
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2answers
79 views

Can censored data act as the dependent variable for a logistic regression?

I need to do the research about the risk factors that contribute to heart failure. The data I have just the censored data with some risk factors of heart failure. And I need to use logistic ...
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44 views

How to do “partial” survival analysis on randomly censored data?

Suppose that we monitor a population of devices over an interval $[a,b]$. Some devices are added before $a$ and some are added during $[a,b]$. Furthermore, some devices fail during $[a,b]$ and some ...
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64 views

Censored regression with Poisson distribution

I am trying to fit a Poisson distribution for left censored data. Let $x_1,x_2,...x_n$ be the observations with the first $r$ observations being less than the threshold of $c$ and hence censored. The ...
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120 views

ggsurvplot for counting type data showing censoring of all at risk subjects?

I've been trying to create KM plots using the R packages survminer and survival for counting type data. I have the following columns, ...
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38 views

parameter estimation using censored data by fitting a Maximum likelihood to a differential equation

I have a population data ($N$) measured over certain time points ($t$). The rate of change of the population is modelled as a ODE as, ${dN\over dt}=-\lambda N$ My intention is to estimate the ...
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11 views

Parametric estimator for straightforward interval-censored data

$X_i$ is iid from some distribution, such as $N(\mu, \sigma^2)$. All I want is to estimate the parameters of the distribution. However, I don't observe $x_i$, instead, I observe $(a_i, b_i)$ such that ...
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44 views

Distribution of shifted and censored random variable

Suppose I have a non-negative random variable $X$ with finite mean $\mu$. Let's for example assume it denotes demand, and we denote by $X(t)$ demand in period $t$, demand in different periods are iid. ...
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85 views

Multi State Models to analyze/plot disease progression and probability of being misdiagnosed

Let's say that I have the following dataset containing information for 100 patients that have been followed up for a certain number of years to check if they develop a certain disease. We know up-...
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10 views

Correct Specification for Censored Data

I have some construction data, which shows the starting year of unfinished and finished projects but don’t have any information on the completion time of finished projects. If I had data on the ...
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19 views

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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81 views

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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26 views

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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1answer
49 views

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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9 views

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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21 views

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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23 views

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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1answer
40 views

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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75 views

Calculate E[X] from incomplete data?

The exercise I'm doing describes the random variable $X$ as the following ...