This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 360
Type: Contributed
Date/Time: Tuesday, August 3, 2010 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #308747
Title: Power in the Case of Extreme Bimodal Distribution: Analysis of Delirium/Coma-Free Days in the ICU
Author(s): Jennifer L. Thompson*+ and Ayumi Shintani
Companies: Vanderbilt University and Vanderbilt University
Address: 1161 21st Avenue South, S-2323 MCN, Nashville, TN, 37232,
Keywords: bootstrap ; proportional odds ; nonparametric ; regression ; simulation ; bimodal

When data are complex, statistical methods considered most correct may produce results which are not easily interpreted by clinicians, making choice of analysis difficult. We consider data measuring acute brain dysfunction among critically ill patients. Severity of dysfunction was quantified as number of days alive and without delirium or coma over a 14-day study period; this variable often creates clusters at both minimum and maximum values, making normalization of data challenging. Proportional odds models are useful, but results can be difficult to express to clinicians. We present a simulation study to compare the power and relative benefits of the Wilcoxon rank sum test, proportional odds logistic regression, and bootstrapped linear regression - all robust to distribution assumptions - in detecting differences in outcomes between two treatment groups, using normal and bimodal data.

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