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Questions tagged [survival]

Survival analysis models time to event data, typically time to death or failure time. Censored data are a common problem for survival analyses.

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Newton-Raphson on Cox PH

I am currently working on my research, namely comparing the conventional optimization method, namely Newton-Raphson, in estimating Coxph parameters with the SGD optimization method. What if I want to ...
Dion Orlando Sitohang's user avatar
3 votes
1 answer
262 views

Competing Risks that are not mutually exclusive in Survival Analysis

I have 5 type of events that a subject can experience. However, not all these events are competing with each other: For the events A, B, C, D, E; occurrence of A blocks B from happening. B, D and E ...
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1 answer
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Is differential follow up periods in survival analysis a problem?

I'm looking to compare mortality post-operatively following two different surgical techniques. due to technological advances, one of these surgical techniques was only performed around five years ...
MFA's user avatar
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Data preparation for multistate modelling

I need to use multi-state modelling using Stata Software for which I need to prepare the data. My data consists of disease diagnosis and dates of diagnosis. I need to understand how can I create the ...
Sobia Ambreen's user avatar
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Dealing with non-proportional hazards in a Cox model with many variables and a large dataset [closed]

I am trying to check whether some variables violate the proportional hazards assumption in a Cox model on a large dataset. I am using R and the survival package. ...
Thomas's user avatar
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Plot Hazard ratio, 95% CI with a continous variable

Can R generate some figure like this? x-axis=age(continous), y-axis = hazard ratio for each count? Our dataset: mydata, event=death, time to event=years, var=age, group=treatment(1) vs control(0)
bigbigtree's user avatar
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1 answer
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Perfusion Analysis Counts as Survival Analysis?

In perfusion analysis, the patient is injected with some dose of medicine. A machine detects, over time, the dose of medicine in the patient's body. In other words, the data for each patient is time ...
温泽海's user avatar
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2 answers
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Limited outcome events. Choice of method

I´m running a study on rare events. I compare two groups A (n=50) and B (n=200) but I found fewer outcome events than expected, A (n=12), B (n=4). Can I use this data for any meaningful purpose or is ...
hklovs's user avatar
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5 votes
1 answer
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How can a hazard function be negative?

I've been reading through Survival Analysis in R, an ebook that I found for independent study, and have run into a point of confusion. They define the hazard function as follows: where T is whichever ...
js4032's user avatar
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1 vote
1 answer
33 views

Optimal sequence analyses and hypothesis testing

I am working with data in R using the TraMineR package. I am fairly new to this type of analysis, so please bear with me. I have a list of unique states (Ex: "NN", "s2s", "...
user17451520's user avatar
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Survival analysis: usage of local control and local recurrence free survival [closed]

I noticed that in some publications the terms "local control" and "local recurrence free survival" are used interchangeably, in others the local control does not include the death ...
Elias's user avatar
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2 votes
2 answers
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Defining clinical follow-up: Fixed Period vs. Maximum Duration

We are retrospectively analyzing data of around 1100 patients operated between 2017 and 2023. We analyzed follow-up documentation until 2024. This means that patients operated at a later date will ...
Philipp's user avatar
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1 vote
1 answer
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Hazard Ratio from two cox models

I am working on a dataset from a clinical trial where patients received either treatment $A$ or treatment $B$. My goal is to develop two separate Cox proportional hazards (PH) models: one for patients ...
Igna's user avatar
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1 answer
33 views

Estimate Weibull Shape and Scale function from lifetable data in R

I am trying to calculate a Weibull function departing from an actuarial life table using R. I have tried to transform life table data into individual patient data and then fit a Weibull using flexsurv ...
r1000's user avatar
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2 votes
1 answer
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Forecasting Survival Analysis

I use the Kaplan-Meier estimator to represent survival functions between two groups. Suppose I have X events at a given time t. How can I predict time t+k to obtain X+i events? As with time series, is ...
Guillaume's user avatar
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1 answer
27 views

Time related categorical variable for cox regression

I am trying to fit a Cox regression model to my time-to event data and besides other subject specific variables, I have two specific calendar dates that I want to analyze the effect of. For these two ...
smgtkn's user avatar
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Hazard ratio scale to Z-score scale - Freidlin Boundaries

In the paper A general inefficacy interim monitoring rule for randomized clinical trials, they propose boundaries for interim analyses using the hazard ratios. These boundaries are illustrated in an ...
Márcio Augusto Diniz's user avatar
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How should stratification factors be accounted for in analysis?

In the context of a clinical trial with time-to-event primary endpoint, if stratified randomization is used for subject enrollment, how should the stratification factors be accounted for in the ...
Will_Zhang's user avatar
1 vote
1 answer
50 views

Dropping a level of a categorical variable with small number of subjects on cox regression

I am trying to fit a Cox regression model to my time-to event data and have a categorical variable with 5 different levels. I leave one level out as the 'reference'. I also have 2 levels with small ...
smgtkn's user avatar
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1 answer
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Dealing with categorical variables on cox regression

I am trying to fit a Cox regression model to my time-to event data and have a categorical variable with 5 different levels. If I don't leave one of the levels out, then I will have multicollinearity, ...
smgtkn's user avatar
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Conditional Logistic (Discrete Cox PH) Regression Model

I am very new on the topic of disc påret time survival modeling. I found the following function in R from package powerSurvEpi. It seems that powerConLogistic.bin function can be used for #Sample Size ...
elisa's user avatar
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1 vote
1 answer
79 views

What's the gain from multistate model comparing to transition specific survival models?

Currently I'm working on multistate patient data, where patient transitions into states are observed at exact, irregular occasions. However discharge times from the states are unknown. Patients can ...
Tom's user avatar
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0 answers
15 views

Baseline covariates with age as time scale in survival analysis

I’m looking for the correct way to incorporate baseline information in a survival analysis when using age as the time scale (or confirmation that what I'm saying in the following is correct). Clearly, ...
LucaS's user avatar
  • 771
1 vote
1 answer
31 views

Considering 96 observation for estimating the intercept (rule of thumb)

I remember Prof. Frank Harrell stated that in order to calculate the sample size using the rule of thumb, we must include 96 observations for just computing the intercept, hence the estimated sample ...
elisa's user avatar
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1 vote
1 answer
39 views

relative Hazard rate

I am still confused about the meaning of hazard rate. I was wondering how I might get the relative hazard rate for the example below (Cox regression). ...
elisa's user avatar
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1 vote
1 answer
36 views

Surival Prediction - Train/Test data vs Production data

I have a need to create a churn prediction model and it seems like a survival model fits the bill since my data is right-censored (there are many customers who have yet to churn, or in other words, ...
QuantumGizmoExplore's user avatar
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0 answers
16 views

Dealing with Low variance categorical variables on cox regression

I am fitting a time varying cox model to my survival data, and I remove one arbitrary level from each categories, to create the baseline hazard. I have some low variance categorical variables. If I ...
smgtkn's user avatar
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0 answers
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Merging Different Groups for Cox Regression

I have time to event data for subjects from different groups, and I use group features as covariates for cox regression. For example, I have 100 subjects from group A, and 200 subjects from group B, ...
smgtkn's user avatar
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2 votes
2 answers
43 views

Interpretation of hazard ratios - impact on time to event?

say I use Cox proportional hazards model where I explain time to some event with a number covariates. In the result, for each covariate I get the proportional hazard ratios (HR). A HR lower than 1 ...
chris_chris's user avatar
2 votes
0 answers
14 views

Cox regression curves or Kaplan Meier?

Why not just present the survival curves from Cox cox survival regression analysis instead of Kaplan Meier curves?
LeeTi's user avatar
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1 vote
0 answers
31 views

need a clarification about the meaning of Hazard rate (ratio)

I found the following formula for calculate the number of event. I was wondering if RH refers to hazard ratio or hazard rate (For me, it seems that these two should be different. Please correct me if ...
elisa's user avatar
  • 55
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0 answers
12 views

Time-varying coefficients based on binary variables

I am doing a survival analysis, and for each individual i have one event occuring (the one of interest), then i have baseline events (inc1 & ...
BPeif's user avatar
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0 answers
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Vertical Lines in Proportional Hazard Assumption Test

I ran a Anderson-Gill survival analysis. When checking if the proportional hazard assumption is met, I got the following plot: The Betas at the very of end of my study are for sure wrong. What did I ...
Sven Prüß's user avatar
1 vote
1 answer
47 views

Survival analysis - any benefit to splitting on failure time instead of covariate change for creating time-varying covariates?

When needing to create a time-varying covariate for a survival model, I am accustomed to using (what I understand to be) a counting process structure for my data, where each individual may have ...
LucaS's user avatar
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1 vote
1 answer
44 views

Correct interpretation of survival curves that eventually meet

I have some survival data that we are trying to analyse and make sense of. The outcome is a progression in disease status. The primary exposure is time-varying in nature - initially unexposed, but ...
LucaS's user avatar
  • 771
4 votes
1 answer
148 views

Interpretation of R output for stratified cox-ph model

For the following model: model <- coxph(formula = Surv(time, status) ~ treatment * sex + strata(sex), data = data) this is (part of) the model summary in R: ...
user412691's user avatar
0 votes
1 answer
38 views

Validity of disease duration variable in survival analysis

I am wondering about the validity of including a 'disease duration' variable in a cox model, when the disease duration is measured from the start of observation (i.e. at the point of diagnosis)? This ...
LucaS's user avatar
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0 answers
38 views

GAM analysis two ways: as percent survival using normal dist and as alive/dead using binomial dist but getting drastically different results

My question relates to salmon population data. Im trying to understand how ocean variables affect the return of salmon. Ive analyzed the data two different ways. The first, the response variable as a ...
Don Segundo's user avatar
1 vote
1 answer
142 views

Regression spline for time to allow for slope changes

Suppose we have a regression / survival model where we would like to model follow-up time using a regression spline. Follow-up time has two phases (first treatment active, and second treatment ...
user167591's user avatar
1 vote
1 answer
52 views

discrete time model and Logistic regression

To analyse discrete time cox PH (including time varying covariates), the following R function can be used: glm (family = binomial, link = "cloglog") Since there is no open formula for ...
Stat2024's user avatar
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1 vote
1 answer
27 views

Understanding Discrepancies Between Frequentist and Bayesian Parametric Weibull Models in Accelerated Failure Time Analysis

Currently in the process of identifying a Bayesian Weibull Survival AFT model that is equivalent to the survreg() Weibull AFT model results from the Survival package in R. I came across this ...
Kosat's user avatar
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1 vote
0 answers
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Is this non-mathematical interpretation of cause-specific vs subdistribution hazards sensible?

I am interested in estimating the risk of readmissions accounting for the competing risk of death. I would like to explain both types of models to people with a basic understanding of statistics. ...
Emily's user avatar
  • 11
0 votes
1 answer
19 views

Multi State Survival Analysis Transition Between States Triggered By different events

I have a state diagram for multistate survival analysis, and between 2 specific states, I have 2 types of transitions triggered by different types of events, i.e, from state 1 to state 2, the ...
smgtkn's user avatar
  • 45
10 votes
3 answers
1k views

How to explain Hazard Ratio in layperson's terms

In the context of a Cox regression, I recently heard someone say that "the hazard ratio of 0.70 between the two treatment groups indicates that, during the whole followup time, of 100 persons in ...
Survival's user avatar
  • 149
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0 answers
13 views

Time-dependent coefficients and its effect on survival after an event

I'm learning about time-dependent coefficients in R using the material below. https://cran.r-project.org/web/packages/survival/vignettes/timedep.pdf In 3.4 PBC data, the code below correctly assumes ...
Toshi's user avatar
  • 1
2 votes
1 answer
86 views

Why are my Hazard Ratio coefficients so large or small in Coxph regression?

I have some grade data for an institution I work at for a specific sub population and comparing it to retention over time. In the first table below are some hazard ratios from a coxph regression in R, ...
Tytalus's user avatar
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1 vote
1 answer
52 views

How to handle zero-inflated time in Cox proportional hazards model with categorical covariates?

I am using a Cox proportional hazards model to compare the time to an event, adjusting for several categorical variables (X1, X2, and X3). One of these variables, X3, is a three-level categorical ...
AziR's user avatar
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0 votes
1 answer
67 views

Lifelines-CoxTimeVaryingFitter for Multistate Survival Analysis

I am new to survival analysis and cox regression, and have limited statistical background. I have time-to event data for a multistate survival model and I want to fit a cox model for each transition ...
smgtkn's user avatar
  • 45
1 vote
2 answers
62 views

Medication use as a time dependent covariate in cox regression?

The goal is to assess how the use of 3 drugs affects the risk of an event. We are using real-life observational data and as such the medications may change during the follow-up time. I am looking for ...
Tasosmav's user avatar
1 vote
1 answer
68 views

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 ...
Stat2024's user avatar
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