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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How to handle intermediate observations in Weibull Models (censoring)
I'm currently working on updating previously created Weibull Models on component failure.
The Situation:
I have data available, that shows if a component of a machine has been exchanged (mainly ...
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impact of time to particular event on response
I am trying to evaluate which variables have the impact on the outcome. My clinical team wants to check if time to particular event has an impact on the outcome. If particular event occured, then time ...
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Inverse probability censoring weighting for selection bias using proc psmatch or any r package
I have a question that it has been proposed that if a treatment causing a censoring, and if there is an unmeasured confounder associated with censoring, as well as the outcome variables.
In this case, ...
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Type of censoring in discrete time survival
*I have a prospective longitudinal study. In this study, the patients come to the hospital every three months for check-ups. T0 ( one week before surgery), T3 (Three months after surgery), T6 (6 ...
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Statistical Non-Response and Drop Out
In statistical studies, it is possible that there might be biases:
Someone groups of people are more likely to be represented compared to others groups of people (e.g. poorer people have difficult ...
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Using time-to-event as a covariate
Techniques to deal with right-censored survival endpoints are well established.
What if I'm interested in using the right-censored survival time as a covariate instead of a response?
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regression when both dependent and independent are both censored
I wonder if there is any technique that measures association between two censored variables. I am given a dataset that includes result from two assays, both of which have a upper detection limit. The ...
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Likelihood function for data with random censoring
The following is from Klein and Moeschberger, p. 76.
Let $(T,\delta)$ be a tuple with $T = \min(X,C_r)$ and $\delta = 0$ if the lifetime X is censored and $\delta = 1$ if it is not; $C_r$ denotes the ...
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Cox Regression: handling immediate drop-outs
In an RCT with two groups, I‘m currently analyzing data using cox regression. While I‘m familiar with the concept of censoring, a rather substantial amount of participants (~32% and 35% in the groups) ...
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Right censoring deaths in length of stay studies
I've been doing some reading on length of stay studies in intensive care units. There are competing events with length of stay and death. For example, a treatment may be more effective at reducing ...
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generalized progressive hybrid censoring scheme type 1 and Muth distribution
I have data concerning failure of sodium sulfur battery cells with the following numeric values: 76,82,210,315,385,412,491,504,522,646+,678,775,884,1131,1446,1824,1827,2248,2385,3077.
This dataset ...
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Is it ok to restrict data to uncensored patient in order to compare models
I have read this answer already "removing-censored-observation". I understand that removing censored data induce a bias in the analysis. But I have somehow a specific case.
I am just ...
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Survival analysis with exclusive censored data
I have a question regarding survival analysis with exclusively censored data
I have a set of 30 observations of length of alcohol abstinence ranging from 1 month to 120 months
The issue with the study'...
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Interpretation question about the article "Finite mixture modeling of censored data using the multivariate Student-t distribution"
I am reading this article and I am struggling to understand the following passage from page 6:
\begin{align*}
L_{i}(\boldsymbol{\theta}|\textbf{V}_{i},\textbf{C}_{i}) = f(\textbf{V}_{i}|\textbf{C}_{i},...
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Modelling Y=min(c,X) for different c
Assume I have a random variable $X \sim Poisson(\lambda)$ which models the potential nr of people entering some room. Now consider this room has a capacity $c$ so that whenever $X > c$ we observe $...
