Thanks for the excellent coverage on competing risks! In Slides 93 & 94 (55:00), it seems to me that the statement should be "A variable that increases the cause-specific hazard may not increase the RISK of the event." as "incidence" is like "rate", based on earlier slides. Am I right?
Absolutely one of the best talks on youtube for survival analysis with competing risks. Cringed with a yikes at the interruption for questions at 55:40 when he is mid-sentence and mid-concept trying to get to cause-specific vs subdistribution etc.
Thanks for this presentation. In the context of bank credit risk: If the primary event is time to loan default and say the the client closes and repays the loan account prior to loan maturity, i.e. loan is repaid and the account is closed (this event happened prior to loan default) and default is thus no longer possible. Is the account closure event a competing risk?
very nice presentation. I have a question about the competing risk in multi-state model. what kind of method is used in multi-state model, cause-specific or sub-distribution hazard model? Or another method?
Multistate models are a framework by which to examine event transitions over time. Survival models are simply a 2-state unidirectional multistate model. Competing risks models are also multistate models. If the question is about regression methods under a multistate framework, then both cause-specific and sub-distribution models may be implemented (similar to other multistate models, such as competing risks models).
how can we calculate sample size for computing risk regression model is it differ from survival technique or different? 2. can we apply competing risk with prediction model in asingle study?
The following is a reply from Dr. Peter Austin. 1. For a cause-specific hazard model, you can use methods that you would for a conventional Cox model. I haven’t seen examples of power calculations for subdistribution hazard models. 2. Can we apply competing risk with prediction model in a single study? I’m not entirely clear on what is meant by this question. One can develop and internally validate a model in a single study. However, one would want to subsequently validate the model in an external sample.
Thanks for the excellent coverage on competing risks! In Slides 93 & 94 (55:00), it seems to me that the statement should be "A variable that increases the cause-specific hazard may not increase the RISK of the event." as "incidence" is like "rate", based on earlier slides. Am I right?
This is one of the best lectures on Survival Analysis.
ppo
Absolutely one of the best talks on youtube for survival analysis with competing risks. Cringed with a yikes at the interruption for questions at 55:40 when he is mid-sentence and mid-concept trying to get to cause-specific vs subdistribution etc.
Excellent, one of the best lectures ever on survival analysis and competing risks. Thanks Peter.
an excellent lecture that saved me during epidemiology class. Thank you !
Outstanding presentation - thank you for posting!
Thank you so much! great lecture
I love this! Thank you so much
Thanks for this presentation.
In the context of bank credit risk: If the primary event is time to loan default and say the the client closes and repays the loan account prior to loan maturity, i.e. loan is repaid and the account is closed (this event happened prior to loan default) and default is thus no longer possible. Is the account closure event a competing risk?
Yes, because default and prepayment are terminal states.
very nice presentation. I have a question about the competing risk in multi-state model. what kind of method is used in multi-state model, cause-specific or sub-distribution hazard model? Or another method?
Multistate models are a framework by which to examine event transitions over time.
Survival models are simply a 2-state unidirectional multistate model.
Competing risks models are also multistate models.
If the question is about regression methods under a multistate framework, then both cause-specific and sub-distribution models may be implemented (similar to other multistate models, such as competing risks models).
how can we calculate sample size for computing risk regression model is it differ from survival technique or different? 2. can we apply competing risk with prediction model in asingle study?
The following is a reply from Dr. Peter Austin. 1. For a cause-specific hazard model, you can use methods that you would for a conventional Cox model. I haven’t seen examples of power calculations for subdistribution hazard models. 2. Can we apply competing risk with prediction model in a single study?
I’m not entirely clear on what is meant by this question. One can develop and internally validate a model in a single study. However, one would want to subsequently validate the model in an external sample.