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A new method for the analysis of time to ankylosis complication on a datasetof replanted teeth is proposed. In this context of left-censored,interval-censored and right-censored data, a Cox model with piecewise constantbaseline hazard is introduced. Estimation is carried out with the EM algorithmby treating the true event times as unobserved variables. This estimationprocedure is shown to produce a block diagonal Hessian matrix of the baselineparameters. Taking advantage of this interesting feature of the estimationmethod a L0 penalised likelihood method is implemented in order toautomatically determine the number and locations of the cuts of the baselinehazard. This procedure allows to detect specific areas of time where patientsare at greater risks for ankylosis. The method can be directly extended to theinclusion of exact observations and to a cure fraction. Theoretical results areobtained which allow to derive statistical inference of the model parametersfrom asymptotic likelihood theory. Through simulation studies, the penalisationtechnique is shown to provide a good fit of the baseline hazard and preciseestimations of the resulting regression parameters.

Regression modelling of interval censored data based on the adaptive ridge procedure