Avtor/Urednik     Maucort-Boulch, Delphine; Roy, Pascal; Stare, Janez
Naslov     On a measure of information gain for regression models in survival analysis
Tip     članek
Leto izdaje     2014
ISSN     0266-4763 - Journal of applied statistics
Jezik     eng
Abstrakt     Papers dealing with measures of predictive power in survival analysis have seen their independence of censoring, or their estimates being unbiased under censoring, as the most important property. We argue that this property has been wrongly understood. Discussing the so-called measure of information gain, we point out that we cannot have unbiased estimates if all values, greater than a given time tau, are censored. This is due to the fact that censoring before tau has a different effect than censoring after tau. Such tau is often introduced by design of a study. Independence can only be achieved under the assumption of the model being valid after tau, which is impossible to verify. But if one is willing to make such an assumption, we suggest using multiple imputation to obtain a consistent estimate. We further show that censoring has different effects on the estimation of the measure for the Cox model than for parametric models, and we discuss them separately. We also give some warnings about the usage of the measure, especially when it comes to comparing essentially different models.
Proste vsebinske oznake     survival analysis
prognosis
informations
analiza preživetja
napovedi
informacije