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A primer of nonresponse in the US Forest Inventory and Analysis programAuthor(s): Paul L. Patterson; John W. Coulston; Francis A. Roesch; James A. Westfall; Andrew D. Hill
Source: Environmental Monitoring and Assessment. 184(3): 1423-1433.
Publication Series: Scientific Journal (JRNL)
Station: Rocky Mountain Research Station
PDF: View PDF (430.17 KB)
DescriptionNonresponse caused by denied access and hazardous conditions are a concern for the USDA Forest Service, Forest Inventory and Analysis (FIA) program, whose mission is to quantify status and trends in forest resources across the USA. Any appreciable amount of nonresponse can cause bias in FIA's estimates of population parameters. This paper will quantify the magnitude of nonresponse and describe the mechanisms that result in nonresponse, describe and qualitatively evaluate FIA's assumptions regarding nonresponse, provide a recommendation concerning plot replacement strategies, and identify appropriate strategies to pursue that minimize bias. The nonresponse rates ranged from 0% to 21% and differed by land owner group; with denied access to private land the leading cause of nonresponse. Current FIA estimators assume that nonresponse occurs at random. Although in most cases this assumption appears tenable, a qualitative assessment indicates a few situations where the assumption is not tenable. In the shortterm, we recommend that FIA use stratification schemes that make the missing at random assumption tenable. We recommend the examination of alternative estimation techniques that use appropriate weighting and auxiliary information to mitigate the effects of nonresponse. We recommend the replacement of nonresponse sample locations not be used.
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CitationPatterson, Paul L.; Coulston, John W.; Roesch, Francis A.; Westfall, James A.; Hill, Andrew D. 2012. A primer of nonresponse in the US Forest Inventory and Analysis program. Environmental Monitoring and Assessment. 184(3): 1423-1433.
Keywordsmissing data, post-stratification, non-sampling error, replacement procedure, bias
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