nonprobsvy: An R Package for Modern Methods for Non-Probability Surveys

Abstract

The paper presents nonprobsvy - an R package for inference based on non-probability samples. The package implements various approaches that can be categorized into three groups: model-based prediction approach, inverse probability weighting and doubly robust estimation. We assume the existence of either population-level data or probability-based population information and leverage the survey package for inference. The package implements both analytical and bootstrap variance estimation for the proposed estimators. We present the theory behind the package, its functionalities and a case study that showcases the usage of the package. The package is aimed at scientists and researchers who would like to use non-probability samples (e.g., big data, opt-in web panels, social media) to accurately estimate population characteristics.