Incomplete Statistical Information Fusion and Its Application to Clinical Trials Data

In medical clinical trials, overall trial results are highlighted in the s of papers/reports. These results are summaries of underlying statistical analysis where most of the time normal distributions are assumed in the analysis. mmon for clinicians to focus on the information in the abstracts in order to review or integrate several clinical trial results that address the same or similar medical question(s). Therefore, developing techniques to merge results from clinical trials based on information in the abstracts is useful and important. In reformation in an abstract can either provide sufficient details about a normal distribution or just partial information about a distribution. In this paper, we first propose approaches to constructing normal distributions from both complete and te statistical information in the abstracts. We then provide methods to merge these normal distributions (or sampling distributions). Following this, we investigate the conditions under which two normal ...

• Type: Conference
• Year: 2007
• Where: SUM
• Authors: Jianbing Ma, Weiru Liu, Anthony Hunter
• Keywords: Clinical Trials, Normal Distributions, SUM 2007, Time Normal Distributions