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.

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Kaplan Meier estimate for data with unequal numbers in treatments

Is it possible to estimate Kaplan-Meier medians, CIs and difference with unequal sample size in treatments or do I have to do coxph? For example, in my dataset, ...
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11 views

Interpretation of non-significant parameters in significant Cox-model as prognostic factors

I want to analyze predictive factors for patient survival after surgery. I have variables that are based on investigations at the time of the surgery, known predictive factors (age, KPS) and data on ...
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15 views

Measuring effectiveness of marketing through attribution analysis

My data(dataframe in R) looks like this:The data is ordered by CustomerName and then TimeofEvent. ...
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1answer
29 views

Data collection process in survival analysis

I must apologize if this seems a very basic question. I am fairly new to survival analysis. Could some please enlighten me on how survival data is collected? I am very much aware of some of the ...
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1answer
17 views

P-value from proportional hazards regression object [on hold]

I'm running some proportional hazards regression models using the survival package in r and would like to know how I can access ...
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28 views

Tail problem with hazard function

Before doing a more advanced survival analysis, I generated an exponentially distributed variable in Stata and used the following code to get a constant hazard rate graph: "sts graph, hazard" I get ...
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20 views

variance-covariance matrix in R for Weibull survival curve

A simple doubt: Can I use values from vcov(ajust) directly? Or do I need some kind of transformation? I mean, for a Weibull model, does ...
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42 views

Plotting Survival Rates For Different Cohorts

I am using Stata 13 to analyze a panel with firm level data. I am estimating a dynamic probit model via the means of xtprobit. During my research I came across Peters (2009) and a very cool graph (see ...
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1answer
12 views

Dummy variables and intercept in Cox regression

I am working with the Cox Proportional Hazards model. Where the covariates include 2 categorical variables. Assume each category has 3 levels, so I model these in terms of dummy variables. Category ...
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1answer
68 views

Cox Regression p-value

I am using R's flexsurvreg function (in the flexsurv package) to fit a AFT model to my data. This is the line of code that fits the model to the data: ...
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1answer
51 views

Comparing failure rates between 2 products with different number of deployed equipment

I have the following scenario, which I am trying to better understand. There are 2 different brands or groups of devices performing the same functionality as such: - Product/Brand 1 has 4,323 devices ...
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17 views

linearized incidence patient-year

I am writhing a manuscript were I have to report according to guidelines the linearized incidence of postoperative complications expressed as % patient-year follow-up. How one can do it in R? Thanks
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1answer
100 views

projecting survival curves estimates into the future

Lets suppose I have a have a survival curve from 0 to 6000 days using Kaplan -Meier curves. How would I be able to project future survival rates from 6001 and forward ? Is there a function or ...
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1answer
36 views

how to interpret log transformed variables in survival analysis?

Suppose I have the following models: fit1 <- coxph(Surv(y,cov)~x,data=records) and ...
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12 views

Survival analysis coxph using ridge regression with 2000 variables => “Penalty terms cannot be in an interaction”

I'm doing a survival analysis using coxph function (package survival). I'm using a ridge regression model included 2000 variables but I have a type of error message "...
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2answers
49 views

Different “end of study” times for different cohorts - Cox PH model in survival analysis

I have a dataset with 4 cohorts of about the same size (~700 people each). I'm trying to apply a Cox PH model using the time needed to pass a very difficult exam as my "time" variable. The cohorts ...
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1answer
23 views

Proportionality assumption test (SAS) for categorical predictors

For Cox regression with all categorical predictors, I want to model time-dependent covariates (time*cov in Proc PHREG) to ...
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1answer
20 views

Can you use event history analysis if your sample was selected on the dependent variable?

I have a dataset that includes a random sample of individuals who are currently in a relationship in the United States. I also have data on the date that they met their partner and the date that they ...
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16 views

Structuring my Survival Model Dataset - Dealing with variables that change

I am working on a survival model where I am interested in how many hours a patient will stay in a hospital. Therefore, the event is Discharge from Hospital. One of the variables I would like to ...
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14 views

Error calculation for survival analysis

I would like to get some support from you concerning the evaluation of standard error associated to survival analysis. I found out that the Greenwood formula can be derived from the Kaplan-Meier ...
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18 views

Cox regression in SPSS and 3 way interaction with two categorical and one continuous variable

I'm new to survival analyses and am trying to test a model that has a 3 way interaction between two categorical variables and one continuous variable. I am concerned I am doing something wrong with my ...
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12 views

Which model approach for data with timings and signals

I have a data set of times, signals and their values. The signals have values from A1 to A6. The first 25 data points of the record are as follows: ...
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28 views

How to tell whether a predictor in a survival model useful?

For the question below (e), I think I need to compare the median survival times for two groups so that I can decide whether AG is a useful predictor. To do so, I wrote the code below, but do not know ...
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54 views

How does left truncation affect the calculation of the logrank statistic for comparing two survival curves?

I'm currently doing survival analysis in R with left truncated data and am having trouble understanding how truncation affects the shape of a survival curve, and the results of a logrank test which ...
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1answer
19 views

LogLogistic Survival Model Assumptions

I am working with Hospital Length of stay data for the first time. It is highly right skewed. In researching ways to approach this problem, I thought a survival model fits the problem description. ...
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9 views

Unbiased weighted average life estimation

I have $N$ subjects. I have $B_i(age)$ - observations of the quantity of interest at the $age$ of the subject $i$. I measure how long this quantity lasts using a weighted average life (WAL) of the ...
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19 views

Cox PH Modelling: How important are ties to the end result?

I am working on create a survival model using Cox PH, but am concerned with the limitation of the continuous time requirement. In my dataset there are often ties. For example, out of 35000 records, ...
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12 views

Weibull regression with survreg function leads to null coefficients

I'm sorry for my English but I'm not a native speaker. I have a pretty big dataset (20k observations) with 15 covariates and 1 response. I noticed that my response seems to have a Weibull ...
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33 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 ...
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51 views

Hazard function, survival function, and retention rate

What is the difference between the hazard function, survival function, and retention rate in survival analysis?
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1answer
28 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 ...
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1answer
32 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 ...
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1answer
20 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 ...
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1answer
15 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 ...
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23 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 ...
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1answer
33 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 ...
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30 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 ...
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47 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, ...
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26 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. ...
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23 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
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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 ...
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12 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 ...
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21 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 ...
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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: $P(X=\{0,1,2,3\}) = (0.40, 0.30, 0.2, 0.1)$ ...
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44 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 ...
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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 ...
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17 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" ...
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1answer
26 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 ...
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1answer
46 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 ...