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prepare_probs_distribution_data ()
Relevant for:
Possible Outputs:
Naive: real_positives real_negatives real_censored real_competing
Adjusted to Censoring: real_positives_adjusted real_negatives_adjusted real_competing_adjusted
The text was updated successfully, but these errors were encountered:
prepare_probs_distribution_data()
Alternative approaches for competing risks:
Key point:
Should I consider Composite as a built-in approach? (tend to yes)
Define the process that will allow all approaches in a unified and usefull manner. Key issues:
One performance data for each approach? (tend to yes)
How to relate to censoring?
Sorry, something went wrong.
create_mids_and_counts_data_from_probs() should produce 1-KM/CIF estimates instead of naive counts in case of adjustment for censoring.
create_mids_and_counts_data_from_probs()
How to consider counts regarding resource-constraint/ppcr?
No branches or pull requests
Relevant for:
Possible Outputs:
Naive:
real_positives
real_negatives
real_censored
real_competing
Adjusted to Censoring:
real_positives_adjusted
real_negatives_adjusted
real_competing_adjusted
The text was updated successfully, but these errors were encountered: