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Activity Number:
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538
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Type:
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Contributed
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Date/Time:
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Thursday, August 2, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #308933 |
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Title:
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Maximum Likelihood Estimation of the Difference between Correlated Poisson Cough Counts
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Author(s):
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Xin Yan*+ and Thomas Bradstreet
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Companies:
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University of Missouri-Kansas City and Merck & Co., Inc.
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Address:
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206 Haag Hall UMKC, Kansas City, MO, 64110,
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Keywords:
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Left truncated Poisson distribution ; MLE ; Correlated Poisson data
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Abstract:
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A statistical method is proposed to assess cough-modifying agents using the difference between cough counts before and after treatment. This clinical endpoint provides a direct assessment of efficacy in cough challenge studies. The conventional clinical endpoint is indirect, specifically the change from baseline in the concentration (either C2 or C5) of inhaled food-derived extract that triggers a predetermined number (either 2 or 5) of consecutive coughs in a given subject. Maximum likelihood estimation of the difference between cough counts before and after treatment is proposed assuming a left truncated correlated Poisson distribution. Estimation of the difference using simulated data is presented to illustrate the method. Two S-Plus functions are provided to facilitate calculating the maximum likelihood estimate of the difference and the corresponding confidence interval.
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