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.

Filter by
Sorted by
Tagged with
0 votes
0 answers
16 views

Diffusion race model with censoring. Help to verify overall logic

I conducted a Go-noGO experiment in which the subject had to press a button if the stimulus on the screen was an orange ($O$) and had to refrain from pressing it if he saw an apple ($A$). The ...
user avatar
  • 663
1 vote
0 answers
35 views

Distribution estimation from interval times

In Formula 1 races, an interval time is the lag behind the leader at a split. If first place completes the first lap at 1:30, second place completes the first lap at 1:32, and third place completes ...
user avatar
0 votes
1 answer
17 views

How to deal with left truncation in cox model in R

I have a longitudinal data with 5 follow-ups. My aim is to see the effect of a disease on ability decline at old age. In my study, I have sibling pairs, one with disease (1) and one without disease (0)...
user avatar
5 votes
2 answers
394 views

Is "Uncensored Data" necessarily more "Informative" when compared to "Censored Data"?

I am told that one of the main benefits of Survival Analysis models are their ability to handle Censored Data. This is in contrast to standard regression models that are unable to do so. For example, ...
user avatar
  • 5,688
1 vote
0 answers
12 views

Missing data, unable to measure

A certain industry specializes in detecting harmful chemicals in drinking water. Let us assume that the goal is to detect lead in drinking water. The instrument used to detect lead has a lower limit ...
user avatar
1 vote
1 answer
37 views

What statistical test compare truncated distribution

I have been taking measures of two populations of mice. One population runs for 10minutes and the other can barely run for 2-3 minutes. The problem is that I have too many mice to keep testing them ...
user avatar
  • 13
8 votes
3 answers
526 views

Is it possible to calculate median value and interquatile range for a set of numbers containing a range or inequalities?

I am trying to make simple median and IQR calculations that involve numbers (in percentages) appearing in a range and inequalities in addition to whole numbers. My sample dataset looks like this: 5, ...
user avatar
  • 85
0 votes
0 answers
10 views

What is the appropriate test for comparing detection times?

I am evaluating different strategies for intermittent surveillance of continuous physiologic processes (e.g., heart rate, with a goal of detecting anomalies in timely fashion without being able to ...
user avatar
  • 1
0 votes
1 answer
35 views

fitting left censored models using software for right censored data

When analyzing a lognormal data with left-censored values using a regression model, I have read that you can use methods that fit right-censored data but “flip” the data by subtracting from some large ...
user avatar
  • 2,262
0 votes
1 answer
15 views

what does the number of censors represent?

I'm trying to understand the ggsurvplot and I stumble about how to interpret the number of censors, like here: why is it 0 at the start and max = 2 halfway through and at the end?
user avatar
  • 2,187
1 vote
1 answer
22 views

How does censoring an observation at baseline impact regression coefficients in survival analysis (e.g., Cox proportional-hazards model)?

I have a dataset with 28000 patients at baseline, of which approximately 1100 have had only a baseline visit. A logical choice would be to censor these observations (0) at time 0. However, I wonder ...
user avatar
1 vote
0 answers
37 views

Survival analysis & Informative censoring: Are these examples in the literature biased?

"Censoring in survival analysis should be “non-informative,” i.e., participants who drop out of the study should do so due to reasons unrelated to the study. Informative censoring occurs when ...
user avatar
0 votes
0 answers
26 views

What is the best imputation method for missing values in compositional data?

I'm a little newbie at statistics, so I'm sorry if my question is too dumb. I'm working with compositional datasets with several chemical elements (continuous data; arranged in columns), but also some ...
user avatar
0 votes
0 answers
17 views

Likelihood for left-censored data in one dimension and uncensored in another dimension

I need to maximize a likelihood for parameters $\vec{\theta}$ given a model $\vec{g}(x_i,\vec{\theta})$ (let's say this is a non-linear black box) and observed data $(x_i,\vec{y}_i)$. The dependent ...
user avatar
  • 1
3 votes
1 answer
88 views

create a zero-censored normal distribution from a normal distribution

Say I have a random variable $X\sim \mathcal{N}(0,1)$. Which transformation do I need to apply to $X$ to get a zero-censored normal distribution?
user avatar
  • 239
0 votes
0 answers
22 views

best use of survey data

So - I am trying to decide which resident to promote. Using their "Performance" as one metric (about 50% of their entire score) My idea was to normalize their survey score and then use that ...
user avatar
1 vote
0 answers
16 views

Conjugacy for right censored data in survival analysis

In survival analysis is it possible to have conjugate priors for the likelihood of right-censored data? More precisely, the likelihood of right-censored data is of the form: $$P(X|\theta) = \Pi _{i \...
user avatar
0 votes
0 answers
12 views

How to summarise mixed binary and left-censored (limit of detection) continuous 'indicator' variables to give read out on continuous latent variable?

I have 4 measures {y1, y2, y3, y4} from n=350 patients, each uses a different method to detect or quantify the presence of the same biomarker, X. I want to estimate the "true" value of the ...
user avatar
1 vote
0 answers
17 views

Estimating demand from partially right-censored sales data

Imagine a company is having limited-time sales events of certain limited editions of their products. Let's consider 3 such events, each featuring a different product, with limited inventory of 600 ...
user avatar
  • 2,454
0 votes
1 answer
29 views

Informative censoring in Regularized Cox proportional hazard model

I am studying Cox proportional hazard models, and in particular Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent, by Tibshirani, Hastie and Friedman. I would like to ...
user avatar
7 votes
3 answers
161 views

Estimating $\theta$ based on censored data when $X_i\sim \text{Uniform}(0,\theta)$ with $\theta\ge 1$

Suppose $(X_i)_{1\le i\le n}$ are i.i.d $\text{Uniform}(0,\theta)$ random variables where $\theta \ge 1$. We observe $Y_i=\min(X_i,1)$ instead of $X_i$. I wish to estimate $\theta$ based on the data $(...
user avatar
  • 9,120
0 votes
2 answers
70 views

How to do LASSO regression with a dependent variable that has two limits

I would like to estimate a LASSO regression for a dependent variable that has a lower limit at -0.661 and an upper limit at 1 in R. I have already estimated a tobit regression without LASSO with the ...
user avatar
  • 109
0 votes
0 answers
26 views

Estimating Right Censored Data

I'm a newbie at Math, and I am just getting my feet wet when it comes to understanding math and statistics so please forgive my ignorance or question if it's already been answered or if materials are ...
user avatar
1 vote
1 answer
31 views

Cox regression where patients have differing follow-up times

I posted a question yesterday and have done some research accordingly, however it has left me with a problem I hope your expertise could be of help: Here is the situation: I am investigating whether ...
user avatar
  • 11
1 vote
1 answer
98 views

Survival analysis: How to code 'left censored' data?

I have data on the closure of brands of stores and I would like to model the factors that influence the risk of closure. I know all the stores that are open on a certain date, 1st January 2015 (but ...
user avatar
1 vote
1 answer
76 views

Goodness of fit of a distribution obtained by minimizing a log-loss function

I am trying to fit a log-normal distribution to a time-to-failure data of a product, but the data to which I want to fit the distribution is not regular data. In the data, every row $i$ has two pieces ...
user avatar
0 votes
1 answer
24 views

How does taking out a group of observations bias your regression?

Assume you have a set of observations at time $t_1$ and you use it to estimate a regression $R1: y=b_0+b_1x$. The regression is used to predict the y-value for the future. You gather a set of (new) ...
user avatar
  • 13
2 votes
1 answer
65 views

Better understanding of censoring and truncation (in particular right truncation) in survival analysis

I am taking a course in survival analysis where we follow the book "Survival Analysis: Techniques for Censored and Truncated Data" by John P. Klein and Melvin L. Moeschberger. Although I ...
user avatar
  • 137
0 votes
0 answers
34 views

Observations for log-likelihood estimation with right censoring

Suppose we have one individual and observe durations between events (visits to a doctor, for example). We make an assumption that durations are independent and distributed to some parametric ...
user avatar
  • 1,054
1 vote
1 answer
28 views

Estimation of parameters in right censored normal distribution

I am working with a subset of a radar image of the ocean, where every pixel has one single value that represents the amplitude. The probability density function (PDF) of the sea pixels can be ...
user avatar
0 votes
1 answer
23 views

How do I incorporate survey data into a survival analysis model?

I'm working with time-to-event data that is right-censored for two different groups. I have administrative data that gives me information on the outcomes and associated covariates. There are a couple ...
user avatar
0 votes
1 answer
99 views

Survival Analysis in the Absence of Censoring

I am interested in better understanding the effects of "censoring" in Survival Analysis. I have heard that two of the main motivations which started the field of Survival Analysis were: 1) ...
user avatar
  • 5,688
1 vote
0 answers
19 views

Random censoring threshold

I am trying to estimate the following censored model: $y_{it}=\beta X_{it} + \epsilon_{it}$. I only observe $y_{it}$ if $y_{it}\leq z_{it}$, otherwise $y_{it}=z_{it}$. The trick is that $z_{it}$ ...
user avatar
3 votes
1 answer
51 views

Left censored index date during survival analysis

I am trying to do a Time To Event analysis, looking at patients with Multiple Sclerosis, which can lead to wheelchair use. My intended study is to look at the time from MS diagnosis to first ...
user avatar
  • 767
1 vote
2 answers
71 views

Probability model for the time to event when the origin is not known

I am interested in a situation when the time to event is observed partially. In the right-censoring situation, we know the start time of the disease $s$ but do not observe the death time $d$, because ...
user avatar
  • 1,054
2 votes
2 answers
68 views

Bayesian estimation of the parameter of a distribution with censored data

I am trying to understand the effect of censored data on parameter estimation, in particular with respect to Bayesian modeling. Here is an illustrating example with some code: Assume you have $N = n+m$...
user avatar
3 votes
1 answer
32 views

Survival Curves with a (potential) intermediate illness

Suppose initially that I am interested in the death rate of males and females that enter a hospital. I could fit survival curves and stratify by group (male or female) and obtain two separate survival ...
user avatar
  • 873
0 votes
1 answer
44 views

Survival Curves using Surv and survfit

I have fit a simple KM curve using the Surv and survfit functions in R. The first 6 rows of the data are shown below alongside the code used to obtain the KM curves. ...
user avatar
  • 873
0 votes
1 answer
148 views

Censoring, truncated and missing data in Survival Analysis

Can someone please explain the difference between censored, truncated and missing data in survival analysis? Suppose I have following information. ...
user avatar
1 vote
1 answer
54 views

Regression model for count data with "endogenously" right-censored data

I have the following problem - I try to estimate a tolerance for negatives from a dataset of subjects. Notice negatives here is a count variable, i.e. it takes on values 0, 1, 2, 3... The data I have ...
user avatar
  • 181
0 votes
1 answer
104 views

Bootstrap for Performance CI with Imputation and Train/Test Split

I am currently performing an analysis in which we are hoping to develop a risk score for a survival outcome using machine learning techniques. Currently, our process is as follows: Split randomly ...
user avatar
  • 5
2 votes
1 answer
104 views

Difference in fitting to right censored data between MLE and Bayesian method

I am fitting a Weibull curve to right censored data. I am doing it by general MLE method using Survival::survreg() as well as Bayesian method using brms::brm. I am pretty sure that I am getting the ...
user avatar
0 votes
0 answers
20 views

Should "rake throw" data be treated as binary, Poisson, interval-censored, ordinal, or...?

I'm currently analyzing "rake throw" data (see here for details), which are a type of data I'm not as familiar with. The gist is that aquatic plant presence and abundance are often estimated ...
user avatar
  • 515
0 votes
1 answer
96 views

Doing MLE when data is missing not at random

Suppose $X, Y, S$, and $Y=f_\theta(X), S=f_\phi(Y), S \in \{0,1\}$. For $n$ data samples, the $y_i$ is only observed for those who have $s_i=1$. That is, we have $\{x_i, y_i, s_i=1\}_{i=1}^{l}$ and $\{...
user avatar
  • 23
0 votes
0 answers
25 views

Sum of Equally Interval Censored Normal Random Variables

Suppose a standard normal random variable $Z\sim N(0,1)$ is interval censored at $[-a,a]$, $a >0$, so that the new censored variate $x$ is $$ x = \begin{cases} -a &z\leq-a \\ z & -a< z&...
user avatar
  • 33
0 votes
0 answers
86 views

Calculating number at risk for Kaplan Meier analysis with staggered entry

I am trying to create KM curves in r on data from a telemetry project. The data is right censored and additionally not all individuals were tagged on the same day so they entered the study at ...
user avatar
1 vote
1 answer
22 views

Baseline adjustment when both pre- and post values are subject to left-censoring

Assume $X$ is a binary treatment variable, $Y$ is a continuous variable measured pre- and post-treatment $(Y_{pre}$, $Y_{post})$, and $Z$ represents the remaining covariates. Both $Y_{pre}$ and $Y_{...
user avatar
1 vote
1 answer
26 views

Censoring for a compount event

I have a data set consisting of patients undergoing a treatment. The data set contains treatment start date, treatment end date, and date of death (if the patient has died). I also have a set of ...
user avatar
  • 470
0 votes
1 answer
33 views

Survival analysis: informative right censored data question

I am attempting to analyze data for someone and am getting stuck on finding something that is appropriate. The design of the experiment is as follows: vials are set up with 10 flies per vial (either ...
user avatar
  • 1
1 vote
0 answers
35 views

Statistical analysis on values that are not exact but above or below a limit (e.g. >100, or <5)

I have a data set with a small number of bioreplicates (3-10) per sample, and I am assessing whether each sample is statistically different from the wildtype control using a Kruskal-Wallis test with ...
user avatar

1
2 3 4 5
9