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Activity Number:
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379
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2007 : 8:30 AM to 10:20 AM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #309135 |
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Title:
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Inverse Prediction: A Clinical Application
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Author(s):
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Jayawant Mandrekar*+
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Companies:
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Mayo Clinic
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Address:
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2665 Boulder Ridge Drive NW, Rochester, MN, 55901,
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Keywords:
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Inverse Prediction ; Regression
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Abstract:
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An important feature of regression methodology is in the area of prediction. Investigators are typically interested in predicting a value of a response variable (Y) based on the known value of the predictor variable (X). However, sometimes there is a need to predict a value of the predictor variable (X) based on the known value of the response variable (Y). In such situations, it is improper to simply switch the roles of the response and predictor variables to get the desired predictions i.e., regress X on Y. This is because the primary assumption that X is measured without error and Y is a dependent, random and normally distributed variable is violated. Inverse prediction is a method that accounts for the underlying assumptions while estimating or predicting X from a known Y. This approach including calculations for the 95% confidence limits will be illustrated using clinical data.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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