Using Auxiliary Population Samples for Sample-Selection Correction in Models Based on Crowd-Sourced Volunteered Geographic Information
利用公民科学项目eBird的成员和一般人口样本，通过有序probit模型估计参与倾向，纠正eBird成员样本中的选择偏差，并应用于分析观鸟者一日出行空间范围。
Data from citizen science (CS) projects (and some social media) can offer selected samples with extensive information about human interactions with the natural world. Independently, we elicit levels of engagement with the eBird project from members of the eBird CS project and from a general-population sample. The general-population sample allows an ordered-probit model to explain propensities to engage with eBird at different levels, which we transfer to predict selection-correction terms for our independent sample of eBird members. We illustrate our method with a question posed only to our eBird-member survey sample about the radii of their individual spatial consideration sets for typical one-day birding excursions.