This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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87
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Type:
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Contributed
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Date/Time:
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Sunday, August 1, 2010 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Nonparametric Statistics
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Abstract - #307410 |
Title:
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A Novel Semiparametric Ratio Estimator: A Key to Predicting Long-Term Weight Loss in Obesity
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Author(s):
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Deborah Weissman-Miller*+
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Companies:
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Dwbus & Assoc. Inc.
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Address:
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26 Calm Court # 5017, Ellijay, GA, 30540, USA
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Keywords:
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Semiparametric ratio estimator ;
change point ;
clinical trials ;
obesity
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Abstract:
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Obesity is a condition of public health significance in the United States. A novel semiparametric survival model is introduced to predict long-term weight loss in obesity from short-term linear regression data. This model introduces the derivation of the highest or lowest F statistic from a linear regression of initial data to determine the location of semiparametric ratio point estimator for long-term predictions. The parametric kernel density function has the form of the cumulative Weibull distribution and is derived from a mechanics model representing human beings. The kernel is given as a ratio multiplied by a prior estimated outcome variable. The results are point estimates at each time-dependent outcome. A real application of this new estimator in clinical medicine and occupational therapy is to estimate long-term weight loss for a single-subject near the beginning of treatment.
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Authors who are presenting talks have a * after their name.
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