On change in length of stay associated with an intermediate event: estimation within multi-state models and large sample properties
This thesis is on the impact of an intermediate on a terminal event. More precisely, it is concerned with quantifying such an impact in terms of (expected) change in length of stay until occurrence of the terminal and associated with the intermediate event. Essentially, we treat the situation as a random time interval problem, with length of the time interval (possibly zero) equal to the time spent in the intermediate state. We suggest and study functionals quantifying change in length of stay. Our approach applies quite generally to functionals summarizing the impact of an intermediate on a terminal event.
biometry, multistate model, nosocomial infection, random time interval
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