3 citations · 4 across the 13 of their papers we have counts for
20 papers
Can we detect treatment effect waning from time-to-event data?
Eni Musta, Joris Mooij
Understanding how the causal effect of a treatment evolves over time, including the potential for waning, is important for informed decisions on treatment discontinuation or repeti…
A mover-stayer model with time-dependent stayer fraction
Eni Musta, Martina Vittorietti
Mover-stayer models are used in social sciences and economics to model heterogeneous population dynamics in which some individuals never experience the event of interest ("stayers"…
Testing for sufficient follow-up in cure models with categorical covariates
Tsz Pang Yuen, Eni Musta, Ingrid Van Keilegom
In survival analysis, estimating the fraction of 'immune' or 'cured' subjects who will never experience the event of interest, requires a sufficiently long follow-up period. A few…
A multiple imputation approach to distinguish curative from life-prolonging effects in the presence of missing covariates
Marta Cipriani, Marta Fiocco, Marco Alfò +2
Medical advances have increased cancer survival rates and the possibility of finding a cure. Hence, it is crucial to evaluate the impact of treatments both in terms of cure and pro…
Testing for sufficient follow-up in survival data with a cure fraction
Tsz Pang Yuen, Eni Musta
In order to estimate the proportion of `immune' or `cured' subjects who will never experience failure, a sufficiently long follow-up period is required. Several statistical tests h…
A two-sample comparison of mean survival times of uncured sub-populations
Dennis Dobler, Eni Musta
Comparing the survival times among two groups is a common problem in time-to-event analysis, for example if one would like to understand whether one medical treatment is superior t…