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An estimation method to reduce complete and partial nonresponse bias in forest inventory

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Abstract

Survey practitioners commonly encounter various types of nonresponse and strive to implement methods that mitigate any resulting bias when reporting results. In national forest inventories (NFI), complete or partial nonresponse usually results from hazardous conditions or lack of plot access permission. While many factors may be related to nonresponse, the two primary factors in the NFI of the USA are public/private land ownership and office/field plot status. To ameliorate potential nonresponse bias, these factors should be accounted for in the estimation process. An estimation method is presented where response homogeneity groups (RHGs) account for differential nonresponse rates between forest/nonforest plots. In a post-stratified estimation context, ratio-to-size estimators are used in RHGs within post-strata to avoid potential bias in variance estimates arising from partial plot nonresponse. Combining RHGs within post-strata requires a complex variance estimator that includes four sources of uncertainty. Testing of the estimation method on a synthetic population showed the approach is essentially unbiased. Application to NFI data from 10 states in the USA consistently showed the RHG method produced state-level estimates of forestland area that were 0.1%–3.6% larger than the current post-stratified estimation procedure. It is suggested that these differences are indicative of the nonresponse bias present when plots having differential nonresponse rates are not accounted for.

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FIA data are publicly accessible; synthetic data on request.

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Acknowledgements

The author is indebted to Dr. Paul L. Patterson for suggesting valuable improvements to the initial draft manuscript. The author is also grateful to the anonymous reviewers for their thoughtful comments to enhance the clarity and technical results presentation.

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Correspondence to James A. Westfall.

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Communicated by Lauri Mehtätalo.

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Westfall, J.A. An estimation method to reduce complete and partial nonresponse bias in forest inventory. Eur J Forest Res 141, 901–907 (2022). https://doi.org/10.1007/s10342-022-01480-6

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