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Mealli, Fabrizia; Pacini, Barbara; Stanghellini, Elena – Journal of Educational and Behavioral Statistics, 2016
Unless strong assumptions are made, nonparametric identification of principal causal effects can only be partial and bounds (or sets) for the causal effects are established. In the presence of a secondary outcome, recent results exist to sharpen the bounds that exploit conditional independence assumptions. More general results, though not embedded…
Descriptors: Graphs, Nonparametric Statistics, Causal Models, Statistical Analysis