The sequence of causes leading to the outcome of interest. In epidemiology and the design of clinical trials, the identification of causal pathways leading to pathology is a major objective. In studying development, normal or pathological, causal pathways can be more readily identified from retrospective studies than from longitudinal data gathered prospectively. Structural equation modelling is one technique that allows (complex) causal pathways to be traced. Problems with demarcating causal pathways involve confounding and the use of surrogate endpoints.<\/p>\n
See Cause (or causal factor)<\/a>, Causality (in philosophy)<\/a>, Confound<\/a>, Confounding variable<\/a>, Diagnosis (or diacrisis)<\/a>, Risk mechanisms<\/a>, Structural equation modeling (SEM)<\/a>, Surrogate endpoints<\/p>\n <\/body><\/html><\/p>\n","protected":false},"excerpt":{"rendered":" The sequence of causes leading to the outcome of interest. In epidemiology and the design of clinical trials, the identification of causal pathways leading to pathology is a major objective. In studying development, normal or pathological, causal pathways can be more readily identified from retrospective studies than from longitudinal data gathered prospectively. Structural equation modelling … <\/p>\n