Missing data usually present special problems for statistical analyses, especially when the data are not missing at random, that is, when the ignorability principle defined by Rubin (1976) does not hold. Recently, a substantial number of articles have been published on model-based procedures to handle nonignorable missing data due to item nonresponse (Holman & Glas, 2005; Glas & Pimentel, 2008;...

congenitally missing of maxillary lateral incisors is one of the most common patterns of hypodontia. this paper presents a nine year old boy with congenital missing of lateral incisors. familial history showed that, his mother, aunts, uncle and grandmother have also congenital absence of lateral incisors.

This article proposes a new approach to extract existing (or detect missing) concepts from a loosely integrated collection of information units by means of concept graph detection. Thereby a concept graph defines a concept by a quasi bipartite sub-graph of a bigger network with the members of the concept as the first vertex partition and their shared aspects as the second vertex partition. Once...

A large body of research has focused on how people exchange and use information during the negotiation process. This work tends to treat information as if it all were readily available upon request. The current research investigated how delays in the pursuit of missing information can influence people’s ex-ante priorities and the final settlements they reach. Study 1 found that negotiators achi...

In a multiple-cue probability learning task, participants learned to use six discrete symptoms (i.e., cues) to diagnose which of three possible flu strains a hypothetical patient suffered from. For some patients, information regarding the status of certain symptoms was not available. Various possible ways in which the missing cue information might be processed were distinguished and tested in a...

The deviance information criterion (DIC) introduced by Spiegelhalter et al. (2002) for model assessment and model comparison is directly inspired by linear and generalised linear models, but it is open to different possible variations in the setting of missing data models, depending in particular on whether or not the missing variables are treated as parameters. In this paper, we reassess the c...