SEQLOGIT: Stata module to fit a sequential logit model. seqlogit fits a sequential logit model. This model estimates the effect of the explanatory variables on the probabilities of passing a set of transitions. For example, given a highest achieved level of education the researcher studies the effect of socio-economic status on the probabilities of passing the different transitions between levels of education. The user can specify any decision tree as long as each level of the dependent variable (e.g. level of education) can be reached through one and only one sequence of transitions. If these levels have values (e.g. years of education) than this model also implies an effect of the explanatory variable on the highest achieved level. The program seqlogitdecomp, which is part of the seqlogit package, displays a graph that decomposes this effect on the highest achieved level into parts that measure the effect on the probabilities of passing the transitions and the importance of each transition.

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  1. Fullerton, Andrew S.; Xu, Jun: Ordered regression models. Parallel, partial, and non-parallel alternatives (2016)