Student success and drop-out predictions have gained increased attention in recent years, connected to the hope that by identifying struggling students, it is possible to intervene and provide early help and design programs based on patterns discovered by the models. Though by now many models exist achieving remarkable accuracy-values, models…

One can distinguish statistical models used in causal modeling from the causal interpretations that align them with substantive hypotheses. Causal modeling typically assumes an efficient causal interpretation of the statistical model. Causal modeling can also make use of mereological causal interpretations in which the state of the parts…

The failure of Hume's "constant conjunction" to describe apparently causal relations in science and everyday life has led to various "probabilistic" theories of causation of which the study by P. C. Suppes (1970) is an important example. A formal model that was developed for the analysis of comparative agricultural experiments…