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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Why are these MLE estimates biased?

I estimate the parameters of survival data with censoring which is simulated from Weibull distribution. The mean time to event was set to 10 by choosing the combinations of shape and scale ...
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20 views

Any reliability conclusion from many duplicate data points?

I'm trying to draw reliability conclusion about a material under a tensile test. All of my data max out the sensor. The spec is 8 lbf and I'm maxing out a 50 lbf load cell. "Get a bigger sensor" ...
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LASSO or other regularized regression with censored (missing) data

Here is my problem. I am looking at various time series curves. Let's call them total spend aggregated over all customers on various products versus time. At any given time, I want to predict the ...
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59 views

High Censoring Rate in Survival Analysis; Much higher survival time among censored patients

I am trying to understand censoring in survival analysis and wondering about how to tell when standard use of censoring breaks down. In one case, the number of censored patients is fairly high (low ...
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110 views

How to cope with missing data in logistic regression?

I'm investigating optimal bidding in auctions, and am using logistic regression to predict the probability of winning an auction given a set of explanatory variables (e.g. the price I bid, number of ...
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16 views

which regression model: nested, censored data

I have the following data structures and would like to know your opinion which regression models are most suitable (and available in R) model 1: - 20,000 cases - nested in 500 spatial units (only ...
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87 views

Random Effects Tobit Model

I'm studying the effect of various criminal case and court district characteristics on sentence lengths. I was planning on running xttobit in Stata because I have individual defendants/cases within ...
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Censored data when censoring time is uneven

I have a data set relating to credit defaults. The data set contains around 100 predictors (some categorical and some numeric). I am interested in predicting the time to default, if the person ever ...
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36 views

How can I estimate the tail of a distribution with a truncated distribution?

The broadband speed data I'm working with have all values over 30Mbps placed into a >30 category. The distribution is thus truncated. This leads to the final column in the histogram below being a ...
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19 views

Finding overall survival in competing risk model

I am dealing with time until event data and there are three types of events that I am tracking Type A Death Type B Death Event C. Type B Death cannot happen unless C happened. At any given time ...
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23 views

R package to handle gene expression and proportional hazards model

I have survival data with RNA expression. A lot of the data is censored. Is there an R package that does a proportional hazards model where the number of covariates is much larger than the number of ...
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13 views

Peformance measure in the case of interval censored data

I am working with real world data which is interval censored data and also with the case of mixed exact observation with right censored data. I would like to know what is the formula of the Hellinger ...
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If $Z_i =\min \{k_i, X_i\}$, $X_i \sim U[a_i, b_i]$, what is the distribution of $\sum_iZ_i$?

Assume the following set up: Let $Z_i = \min\{k_i, X_i\}, i=1,...,n$. Also $X_i \sim U[a_i, b_i], \; a_i, b_i >0$. Moreover $k_i = ca_i + (1-c)b_i,\;\; 0<c<1$ i.e. $k_i$ is a convex ...
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1answer
43 views

Inference with only left-censored data

Suppose I have a data set that is only left-censored data, ex: <5, <5, <5, <10, <10, <10 A technique to handle left-censored data is the Kaplan Meier estimate, see page 5 of ...
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21 views

What is the diff between singly censored and progressive censored data in survival analysis?

I have a question regarding survival analysis . To my understanding, the singly censored data are those if there is one point in time, i.e, say, if the patient died (bulb is still working?) after ...
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132 views

statistical handling of lab values below limit of quantitation (BLQ)

There were several samples BLQ because of the lower limit of quantitation (LLQ) of the method, e.g. 5 ng/ml or less. Using the statistical program PRISM6 I marked these values together with the ...
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Converting a parametric survival model to a cash flow model. How do I account for aging in the population?

I'm building a survival model for time to failure of widgets. Other members of the team want to convert the model to a cost flow model. The basic idea is that we can use the functional form of the ...
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28 views

Is it possible to model BOTH censoring and truncation in BUGS?

Survival times are often right censored and left truncated. From my experience, it does not seem like OpenBUGS allows for both. Truncation is denoted as T( , ) and censoring as C( ,). For instance, a ...
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82 views

goodness of fit for censored data

How to estimate the goodness of fit of a sample containing censored values? There is some older work on the matter (here), but i'd like to know if there is anything more modern. I think a reasonable ...
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46 views

How to treat age-specific left-censored data

I would like to study how the death of a respondent's parent affects his personality (or whatever DV). I have an age of respondent, and also an age when respondent lost his parent. The problem is that ...
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54 views

Censored data prediction

I am working with the survivorship bias free database of hedge funds and trying to estimate the persistence of performance in the future performance of such funds based on the past performance. In ...
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26 views

How to include number of not-yet-decayed radioactive atoms in MLE? [duplicate]

Since this question received absolutely zero attention, here's a complete rephrase with the aim of significantly shortening it. I have a potful of $n$ radioactive atoms. I spend $t_\text{max}$ = 1 ...
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29 views

Appropriate probability distribution for censored ratio data

I have two bacterial markers, I'll just call them X and Y. X codes for virulence, whereas Y just indicates the bacteria is present. Consequently, X will not show up without Y although not all bacteria ...
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36 views

Weighted normal errors regression with censoring

I have some data which I would model via standard multiple regression except: There is censoring (left-censored, fixed but varying censoring points which are known) The errors are assumed ...
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1answer
66 views

Left-censoring in time series data

This is from a Bayesian problem I'm working on. I have worked out \begin{align} f(y_1,...,y_T|\varphi)=f(y_1|\varphi)f(y_2|y_1,\varphi)...f(y_T|y_1,y_2,...,y_{T-1},\varphi), \end{align} and all terms ...
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Factor analysis with severly skewed ordinal data and censored ordinal data

I am aiming to run initial exploratory factor analysis in one sample and then confirmatory in another sample. My indicators are ordinal and so I planned to generate a polychoric correlation matrix and ...
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76 views

Estimate of censored poisson process

I have a set of processes, each of which has number of events and the total length of time. I'm trying to model them as independent Poisson processes with there own rates. The rate of the ith process ...
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35 views

literature on small samples and parametric survival models

I have an abundance of small data sets with right-censored data. There are different groups in each data set and I'd like to get confidence intervals for the regression parameters. Each data set has ...
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83 views

Likelihood of censored data

Let $X_1,X_2,\ldots, X_{n_1}$ be IID with PDF $f(x-\theta) $, for $-\infty<x<\infty$ and $-\infty<\theta<\infty$. Denote the CDF of $X_i$ by $F(x-\theta)$. Let $Z_1,Z_2, \ldots, Z_{n_2}$ ...
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Evaluation of health care program

I'm supposed to analyse the effect of a governmental health care program on mortality (cancer vs. cardiovascular desease vs. any other cause of death). Health care program started in 1975 and is still ...
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45 views

Recovering values from an estimated Pareto distribution

Recovering values from an estimated Pareto distribution A couple of weeks ago I asked a question about the Pareto distribution, wanting to understand how the units of measurement are related in ...
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Estimating distribution from censored data

$X$ is a positive variable with known support (assume discrete support, if that simplifies solution). $Y$ is another variable with the same support. $X$ and $Y$ are independent. $Z$ is equal to $X$ ...
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Likelihood Function for Censored Structural Model

I am estimating a structural model with the following data generating process: $$x=\begin{cases}\begin{array}{c}y-\theta\\0\end{array} & \begin{array}{c}if\ y>\bar{y}(\lambda_1)\\if\ ...
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293 views

Can Kaplan Meier method be used to estimate left-censored data?

I have a set of 1000 datapoints of measured concentrations that may include up to 300 values which are censored (below the detection limit that the lab could reliably measure). The range of detection ...
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40 views

Deriving the distribution of the sum of censored variables

I want to be able to calculate the distribution of $$Y = \sum_{i=1}^n\max\{0,X_i\}$$ where the random variable $X_i\sim N(\mu_i,\sigma_i)$. Is the calculation of $f_Y(y)$ possible and if so what is ...
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169 views

Joint pdf of a continuous and a discrete rv

Let us consider a manufacturing system. It involves 2 independent components. If one of these components fails then the entire system fails. Let $Y_j$ be distributed $\exp(Q_j)$ where $j=1, 2$. If ...
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45 views

Comparison of cell counts with a right censoring

I have cell counts related to the action of different microorganisms and I want to compare their distribution. It's supposed they follow a normal distribution after a log transformation, but I can't ...
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57 views

Estimate the parameters of beta exponential distribution via L-Moments

Estimate 3 parameters of beta exponential distribution in the case of censored type 1 samples via L-moments
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335 views

Right-censored survival fit with JAGS

Update: I got the JAGS model running and this eliminates the distracting part of my question. It's really about the proper preparation of data for dinterval() and inits. I can't find a concrete ...
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Top-coded survey data

Top-coded income data are often modeled with a Pareto distribution, but that is controversial. What would be wrong with declaring those values as missing and then using multiple imputation (MI) to ...
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1answer
1k views

Difference between independent and non-informative censoring

I was wondering if I could get a third opinion to settle a discussion on the distinction between independent and non-informative censoring. My definitions: 1) In independent censoring, the event ...
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Get a desired percentage of censored observations in a simulation of Cox PH Model

This question comes from: How to simulate a Cox proportional hazards model with change point and code it in R (See answer) I want to generate a censoring variable $C=Exponential(\theta)$ that create ...
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left-censored dependent variables and prediction

I'm coding up a monte-carlo analysis; I've got a deterministic model that depends on parameters that are uncertain. One of those uncertain parameters is a partially-observed vector of prices by ...
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Estimating a distribution from above/below observations

Let $P$ be an unknown distribution on $(-\infty,\infty)$. Let $X_1,\ldots,X_n$ be an iid sample from $P$. Let $c_1,\ldots,c_n\in(-\infty,\infty)$ be a known set of constants. We observe ...
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451 views

High censoring rate in survival analysis

I have some data which I've analyzed using Kaplan Meier estimation. However, I have a gut feeling that this estimator is biased due to the high censoring rate in my data (nearly 50% censored at later ...
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Name of phenomenon on estimated CDF plots of censored data

My dataset contains two (rather strongly correlated) variables $t$ (runtime of algorithm) and $n$ (number of examined nodes, whatever). Both are strongly correlated by design, because the algorithm ...
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Estimating right-censored data

I am VERY new to stats. I have a large amount of life-time data (delay in arrival since start of experiment) from repeat experiments. Some data is missing, but essentially represents a delay longer ...
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301 views

Finite mixture models with bounded data

I am trying to fit a finite mixture model to a dependent variable which is bounded (practically) between -0.594 and 1 (theoretically, the latent variable is bounded between -Inf - 1). The data are ...
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Accelerated Failure Time scale parameter excessively large when data is right censored

I am using an accelerated failure time model with the Weibull distribution to predict failure times. My failure times range from 1 - 365, with many (80%) data points that are right censored (no ...
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347 views

How to model a bounded lognormal dependent variable with many zeros

I try to analyze firms´ investment decisions. In my dataset 70% of the firms choose to invest 0 $ . 30% invest more than 0. (continuous variable). The data of the 30 % is log normally distributed. ...