Survival Analysis
16 important questions on Survival Analysis
Types of survival data:
- Inflow sample
- Outflow sample
- Population sample
OLS regression model survival analysis:
Where can OLS not account for?
- Time varying covariates
- Duration dependence
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Properties survivor function:
S(0)=1
lim t -> inf S(t) = 0
dS/dt < 0
Negative duration dependence:
Survivor function S(t):
Where is the hazard rate similar to:
Transformation hazard rate:
What kind of estimator is the KM estimator?
How can the KM estimator be interpreted?
Specifications of hazard functions:
- Weibull: labda(t)=gamma*alpha*t^(alpha-1), S(t)=exp(-gamma*t^alpha)
Appropriate likelihood contributions:
- Left truncated at tL: f(ti)/S(tL)
- Left censored at TcL: 1 - S(tcL)
- Right censored at TcR: R(tcR)
- Right truncated at tcR: f(tR)/(1-S(tcR)
- Interval truncated: S(tcL) - S(tcR)
How can we account for observed heterogeneity between individuals?
Interpretation hazard coefficients:
What does the Cox proportional hazard model do?
Approach Cox proportional hazard model
2. At any point of time tj the set of observations that are at risk will be R(tj).
3. Conditional probability of tailing at time tj is:
P(Tj=tj|R(tj))=exp(xj'beta)/sum exp(xl'beta)
The question on the page originate from the summary of the following study material:
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