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Activity Number:
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596
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 6, 2009 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Survey Research Methods
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| Abstract - #304576 |
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Title:
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An Improved Imputation Methodology Derived Through Regression Trees
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Author(s):
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Pedro J. Saavedra*+ and Paula Mason and Benita O'Colmain and Jeffrey Foarde
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Companies:
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ICF Macro and Energy Information Administration and ICF Macro and ICF Macro
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Address:
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11785 Beltsville Drive Suite 300, Calverton, MD, 20705,
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Keywords:
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exponential smoothing ; petroleum surveys ; trend adjustments ; periodic surveys
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Abstract:
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The EIA collects monthly information on the balance between supply and disposition of crude oil and petroleum products through a family of surveys. The process requires all imputed values to be available before responses are received, but uses values for only select cells. Previous analysis led to the recommendation for some surveys to implement an imputation method using historical values obtained through exponential smoothing and trend adjustments from a weekly survey. One survey was particularly difficult to resolve because of more extensive dimensions of the survey, the many cases of zero values, and fewer comparable cells in the weekly survey for trend adjustment. To group cells, a regression tree method (CART) was used to obtain groups for which the same smoothing coefficient could be used. Simulation analyses were then conducted to identify an optimal coefficient for each group.
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