CONFIDENCE INTERVALS FOR POWER,WITH SPECIAL REFERENCE TO MEDICAL TRIALS*

A technique is given for drawing valid inferences in cases where performance characteristics of statistical procedures (e.g. power for a test, or probability of a correct selection for a selection procedure) depend upon unknown parameters (e.g. an unknown variance). The technique is especially useful in situations where sample sizes are small (e.g. in many medical trials); the “usual” approximate procedures are found to be misleading in such cases.     

Qualitative computing: Approaches and issues

This paper reviews three approaches to using computers to perform qualitative analysis. These approaches are distinguished by the way they represent knowledge in the computer—as text, things, or concepts—and the operations they permit on that knowledge. These approaches are compared and the advantages and disadvantages of each are identified based on the way they perform basic tasks of qualitative research. Finally, fundamental issues and problems likely to influence qualitative computing for years to come are discussed.This research was conducted while the author was on sabbatical leave from the University of Missouri and a post-doctorate fellow on NIH grant LM 07006 from the National Library of Medicine. This paper has benefited greatly from the comments of Peter Hall.