Survival analysis is concerned with modelling the time before subjects change state, typically time until death or failure. One key feature of such data is that they can be censored, that is, some subjects will not have changed state before the study ends.

learn more… | top users | synonyms (1)

0
votes
0answers
8 views

How to demonstrate biased estimates of linear regression vs cox proportional hazard survival analysis in R?

I want to perform a really simple simulation of right censored data. Then I want to draw a kaplan meir survival curve and do a cox proportional hazards test. Then I also want to perform a simple ...
0
votes
0answers
16 views

Hazard function, survival function, and retention rate

What is the difference between the hazard function, survival function, and retention rate in survival analysis?
1
vote
1answer
15 views

How do you compare two “survival times” when there is no censoring per se?

I've gone through the 70+ questions when using "survival no censoring" as my search criteria, but I can't seem to find an answer to this very simple situation. I have patients' length of stay in a ...
1
vote
1answer
27 views

Some doubts about survival analysis

I'm struggling to perform a correct and unbiased survival analysis, but I have some doubts. Data I observe a population of posts on a blog within a temporal window $[T_{0}, T_{final}]$. Each post ...
2
votes
1answer
19 views

Approach for estimating expected time required (Regression analysis)

I am analyzing data from a factorial experiment with between subject factor Purifier (two types A and ...
0
votes
1answer
13 views

Time to event with a discrete number of time points

I'm planning a clinical study, in which my desired primary outcome is time to event. My new treatment is non-inferior to the current one in it's therapeutic abilities, however it makes an impact much ...
2
votes
0answers
20 views

Survival analysis with time dependent covariates and cured fraction

I have a problem specified in this way, I'll make a fictional example, because the actual data requires quite a bit of domain knowledge to be understood. There is a series of newborn babies (let's ...
0
votes
1answer
27 views

Combining Force of Mortality for F and M to find $l_x$

So I have the definition of the force of mortality as $\mu_x=-\frac{1}{l_x}\frac{d l_x}{dx}$ and I am given two different forces of mortality, one for females as $\mu_x^f=0.05(1.2)^x$ and the other ...
0
votes
0answers
17 views
0
votes
0answers
17 views

R: dichotomous time interaction in a Cox model

I am using the Cox proportional hazards model to estimate adjusted hazards ratios for survival data. My main effect violates the proportional hazards assumption. I understand there are several ...
0
votes
0answers
10 views

How to calculate linearized rate of postoperative complications in % patient/year in r [closed]

Linearized rate is a method summarise constant hazard function in a very simple way and defined as: total number of observed events divided by total patients-year (person-year). These rates should be ...
0
votes
0answers
34 views

Modelling proportional hazards in Cox Model using coxph in R

Assume I have a heterogeneous sample with two categorical variables A and B, each with 2 levels. Now I want to measure the effect of these on the survival function. So we assume proportional hazard, ...
2
votes
0answers
11 views

Restricted mean survival time with stpm2 in Stata: No confidence intervals after margins command

I want to calculate restricted mean survival time using stpm2 and margins in Stata. ...
0
votes
0answers
19 views

Where can I find time-to-event/survival analysis datasets?

I have a problem finding datasets that could be used for time-to-event/survival analysis. Could you recommend any good sites? I'd be grateful. Dan
0
votes
0answers
14 views

how can I save the survival probability that used to calculate NRI for an indiviual?

I am trying to save the survival probability that used to calculate NRI (i.e. in the survIDINRI package) for an individual. and I wanted to use these probabilities to further analyse what kind of ...
1
vote
0answers
11 views

How to model cumulative risk over a baseline with multiple events in time series data

Suppose I have patients with these events (at varying/individual times): change in insurance change in Health care provider adverse event late prescription fill missed prescription fill I also ...
0
votes
0answers
17 views

Time sliced models for time dependent event

For time-dependent event modeling, we may do time -sliced classification models to predict event(yes or no). For the whole data set, the claims( in my data) are censored at different times. I can ...
1
vote
0answers
25 views

Mean residual lifetime divided by odds of survival?

Is there a name for the mean residual lifetime divided by odds of survival? Does it have an intuitive meaning or interpretation? Example: $P(X=\{0,1,2,3\}) = (0.40, 0.30, 0.2, 0.1)$ ...
1
vote
1answer
42 views

Dummy variable trap in survival models

I am familiar with the dummy variable trap in normal OLS, in which we should include one less dummy variable than the total of categories to avoid the problem of multicollinearity. However, I was ...
0
votes
0answers
17 views

Can you have a “partial death” event as censored variable in survival analysis?

I am working on a dataset in which most of the patients encounter 'partial' death(the variable is in the range[0,1]) before censoring happens. Currently, I applied a proportional hazard model by ...
1
vote
0answers
16 views

Confidence intervals and functions of an estimator

Im studying non-parametric estimators for survival functions and for the Nelson-Aalen estimator we have that the estimator for the survival function is exp(-Y_hat) (i.e. exponential of negative "y" ...
2
votes
1answer
24 views

Why is estimating the standard error of an estimate that is itself the product of several estimates so difficult?

Singer and Willett (2003) write the following about estimating the standard errors of estimated survival probabilities within the context of discrete time event history models (e.g. logit hazard ...
2
votes
1answer
41 views

Survival estimation when death/censoring is probabilistic

I am trying to estimate survival function, but in case where each event is censoring with probability $p_i$. (That is, I am never sure if the event is right-censoring or death, but I can estimate the ...
1
vote
1answer
54 views

Setting up dataset for Cox regression with time-dependent variables

I posed a question about how to set up the code for this question here (SAS/proc phreg code) and @Fomite suggested that I pose a separate question about whether my data are set up correctly. ...
1
vote
1answer
42 views

SAS/proc phreg code

Background: I'm studying people seeking help. Participants described contacts with between 1 and 3 "responders" (e.g., friends, the police) in order- for example, a participant could have contacted ...
4
votes
1answer
83 views

Relationship between hazard function and survival function in the presence of censoring

In survival analysis there is a relationship between the survival function, $S(t)$ and the hazard function, $h(t)$, in that $$ h(t) = -\frac{d}{dt} \log S(t)~~~~~~~~~(1)$$ from which we can form the ...
0
votes
0answers
26 views

How to interpret the overall model output of a Cox model?

I am running Cox regression analysis. I have read FOX's manual and I understand how to interpret the output of each predictor. But I am not sure how I should be interpreting the overall model output, ...
1
vote
1answer
41 views

How to compare means, variances and standard deviations of durations for statistical significance

I am trying to compare multiple mean values, variance and standard deviation values for statistical significance. For example I have the following data: Data 1 Mean: 0.01304 Sample ...
0
votes
0answers
6 views

Best approach for using predictive anlaysis to improve upon survivalist data

I previously have done alot of work on Arrhenius modelling in JMP using Censoring data variables. The factor that causes accelerated failure rates is Temperature and so the activation energy function ...
0
votes
0answers
32 views

Survival Analysis Cox Ph Predict values

I'm coming with a question that I think is easy for most of you. But as I'm a newbie in Survival Analysis (I started 2 days ago), I can't figure out how to do it. I'm given a data set on ...
1
vote
1answer
14 views

Parametric Estimation of Incomplete survival data/observation

Are there other methods besides the Maximum Likelihood for estimating parameters in an incomplete data when a parametric distribution is assumed?
0
votes
0answers
18 views

Survival predictions in multistate models

Consider a scenario in which individuals can cycle between multiple states, and eventually either die or exit the study (right censoring). We observe time varying covariates when a subject enters the ...
0
votes
0answers
11 views

Cause-specific hazard in R

library(cmprsk) library(muhaz) set.seed(2) time <- rexp(100,2) cause <- sample(0:1,100,replace=TRUE) mod = muhaz(time,cause) plot(mod) The above R code ...
2
votes
0answers
27 views

Validate predictive power of Cox proportional hazards for individual observations

Note I've edited the example to be more intuitive and closer to my real data Intro I've got data on customers purchases and with it am trying to predict which customers are more likely to make next ...
0
votes
0answers
10 views

Conditional expectation in mixture distributions

I have a mixture distribution for observed lifetime data $(\delta_i,t_i,L_i)$, where $\delta_i$ is a censoring variable (1 indicating death, and 0 indicating censoring), $t_i$ is the observed lifetime ...
0
votes
2answers
56 views

Lifetime or Failure Time

Lifetime / Survival time / Failure time : the time to the occurrence of event (always nonnegative) . Lifetime and Survival time can be synonymous . ...
0
votes
0answers
5 views

Regional differences; how to express odds and hazard ratios as a comparison 'to the mean'

I am doing an analysis where I look at the proportion of patients receiving a specific treatment within a specific period. I know there are sex and age effects. I am interested in regional ...
1
vote
0answers
27 views

Difference between Cox Proportional Harzards Model and interval-based logistic model for survival regressions

I have a dataset of timestamped trader transactions (to the second). I want to conduct a survival analysis on the trades where a trade is started at startTime and ...
0
votes
0answers
12 views

Cox MSM or Recurring Event?

I have dataset containing clients' history of active and inactive periods (if there is any) up to present day. Also lots of info as time dependent covariates. I want to model this as MSM, where both ...
1
vote
0answers
42 views

Stata vs. R survival differences; weibull scale is different, problems predicting manually

I am trying to do some survival analysis in R and as a starting point, I want to make sure I can replicate a previous analysis. I notice differences and I will demonstrate them here. I feel like there ...
0
votes
2answers
31 views

Discrete survivor function expressed in terms of hazard

Let $T$ can take on values $t_1,t_2,\ldots,$ with $0\le t_1\le t_2,\ldots,$ and let the probability function be $$f(t_j)=Pr(T=t_j),\quad j=1,2,\ldots$$ The survivor function is then $$S(t)=Pr(T\ge ...
1
vote
1answer
32 views

What model fit / predictive accuracy measure can be used to cross validate a Cox PH model with censored data?

How would you go about validating a Cox PH model with censored data? I am trying to run a Cox PH model on a dataset with observations that failed, and observations that are censored. Normally, I use ...
0
votes
0answers
2 views

Best packages for Cox models with time varying covariates

I am working on a project using Cox models with time varying covariates. My questions are: What are some good examples of conducting this analysis? What is the best R package to conduct this ...
0
votes
0answers
12 views

Modelling credit risk by Ornstein Uhlenbeck process incorporating macro economic variable

I have a data set on default, application score and some macroeconomic variable, I want to model the next default as poison process whose parameter is itself random, it comes from an ornstein ...
1
vote
1answer
32 views

How to calculate adjusted HR?

What is the difference between crude HR and adjusted HR in Cox regression? How do we calculate adjusted HR?
1
vote
0answers
28 views

Can Cox models be used with time-varying covariates?

I work at a hard drive manufacturer. In my project, we have huge sets of testing data of hard drives. Most of them are time-varying covariates. My colleges are using cox regression. I doubt it. ...
1
vote
1answer
23 views

Can two separate regression coefficients be added to estimate their mutual effect?

Let's say I perform a Cox regression including 3 predictors that relate to the survival: Hazard ratios (HR) for predictors Sex: Hazard ratio for males = HR 1.5 Treatment: Hazard ratio for being ...
1
vote
0answers
52 views

Probability distribution of functions of random variables

A system will function as long as at least one of three components functions. When all three components are functioning, the distribution of the life of each is exponential with parameter ...
3
votes
1answer
31 views

Schoenfeld residual independent of time?

I've seen it claimed (e.g. in these notes ) that "Schoenfeld residuals are, in principle, independent of time." Can this be right? Consider the following situation: You are using a Cox model to ...
0
votes
0answers
29 views

How to impute cause of failure with mice?

In survival data, I have a variable cause of death, coded cause 1 and cause 2. Some of the patients are censored and the rest are dead from the cause 1 or 2. I have missing values on cause of death, ...