Boolean Analyzer -- An Algorithm That Uses A Probabilistic Interestingness Measure to find Dependency/Association Rules In A Head Trauma Data

A new, binary-based technique is presented for finding dependency/association rules called the Boolean Analyzer (BA). With initial guidance from a domain user or domain expert, BA is given one or more metrics to partition the entire data set. This leads to analyzing the implicit domain knowledge and creatingweighted rules in the form of boolean expressions. To augment the analysis of the rules produced, we can additionally apply a probabilistic interestingness measure (PIM) to order the generated rules based on event dependency, where events are combinations of primed and unprimed variables. Following our discussion of the basic BA algorithm, our paper will present a case study on clinical head trauma data. BA able to find rules, where the most significant rules were those that had a high PIM. We believe that BA has broad applicability in the medical domain, and hope that our presentation here can stimulate other creative applications of the technique

LONG TERM STUDY OF ACCOMMODATIVE ESOTROPIA*

Purpose: Previous studies of accommodative esotropia have been hampered by biasprone methods of data collection and analysis, and small sample size

The Effect Of Collective Bargaining Legislation On Strikes And Wages

Using Canadian data on large, private-sector contract negotiations from January, 1967, to March, 1993, we find that strikes and wages are substantially influenced by labor policy. The data indicate that conciliation policies have largely been ineffective in reducing strike costs. In contrast, general contract reopener provisions appear to make both unions and employers better off by reducing negotiation costs without systematically affecting wage settlements. Legislation banning the use of replacement workers appears to lead to significantly higher negotiation costs and redistribution of quasi-rents from employers to unions. © 1999 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology