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pubmed:abstractText |
Systematic inclusion of time in observational epidemiological studies may help strengthen the inference to be drawn, but new epidemiological challenges arise, such as time-dependent confounders - covariates which may change from being confounders to being intermediate variables. The focus of this presentation concerns two sets of tools: event history analysis and structural nested failure time models, both applied to a particularly intricate problem in observational epidemiology, of empirically assessing the graft-versus-leukaemia effect after bone marrow transplantation.
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