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Evaluating Trends in Greater Sage-Grouse Populations With Quantile Regression

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By Fort Collins Science Center December 1, 2017

USGS scientists are evaluating the use of quantile regression to develop models of sage-grouse population changes across the United States. 

USGS scientists are evaluating the use of a statistical technique known as quantile regression to develop models of sage-grouse population change. Estimates obtained from quantile regression are less sensitive to a few extreme population counts; can be estimated with an easier, more statistically justified approach to dealing with a few counts of zero; and can be extended to include additional covariates. Furthermore, this technique can provide a robust measure of trends and has fewer statistical assumptions. These features are likely to be especially beneficial in estimating population trends for greater sage-grouse.

USGS scientists are evaluating the use of quantile regression to develop models of sage-grouse population changes across the United States. 

USGS scientists are evaluating the use of a statistical technique known as quantile regression to develop models of sage-grouse population change. Estimates obtained from quantile regression are less sensitive to a few extreme population counts; can be estimated with an easier, more statistically justified approach to dealing with a few counts of zero; and can be extended to include additional covariates. Furthermore, this technique can provide a robust measure of trends and has fewer statistical assumptions. These features are likely to be especially beneficial in estimating population trends for greater sage-grouse.