We show that with a simple normalization of explanatory variables, marginal effects in probit and logit models simplify dramatically, becoming a function of only the estimated constant term. Related simplifications hold for computation of asymptotic variances of these effects. D 2003 Elsevier B.V. All rights reserved.

PURPOSE At stage II surgery during dental implant treatment, early marginal bone loss around the implant occasionally occurs despite a lack of apparent causal events, and the etiology of this bone loss is unclear. This study was designed to investigate whether the bone morphogenetic protein-4 (BMP-4) genetic polymorphism is associated with early marginal bone loss around implants. MATERIALS A...

In this paper we introduce the paradigm of multi-agent causal models (MACM), which are an extension of causal graphical models to a setting where there is no longer one single computational entity (agent) observing or not observing all the domain variables V. Instead there are several agents each having access to non-disjoint subsets of V. The incentive for introducing cooperative multiagent mo...

In this paper we introduce multi-agent causal models (MACMs) which are an extension of causal Bayesian networks to a multi-agent setting. Instead of 1 single agent modeling the entire domain, there are several agents each modeling non-disjoint subsets of the domain. Every agent has a causal model, determined by an acyclic causal diagram and a joint probability distribution over its observed var...

In regression discontinuity models, where the probability of treatment jumps discretely when a running variable crosses a threshold, an average treatment effect can be nonparametrically identi ed. We show that the derivative of this treatment effect with respect to the threshold is also nonparametrically identi ed and easily estimated, in both sharp and fuzzy designs. This marginal threshold tr...

This paper introduces an algorithm that investigates whether the effect of an intervention is identifiable from a multi-agent causal model. A multi-agent causal model consists of a collection of agents each having access to a nondisjoint subset of the variables constituting the domain. Every agent has a causal model, determined by nonexperimental data and an acyclic causal diagram over its vari...

Inconsistencies call for reasoners to revise the information that yields them – but which information should they revise? A dominant view is that they should revise their beliefs in a minimal way. An alternative is that the primary task is to explain how the inconsistency arose. It implies that individuals are likely to violate minimalism in two ways: they should infer more information than is ...