nonprobsampling - Inference for Nonprobability Samples Using Multiple Reference Surveys

Provides pseudo-weighted estimates of means and prevalences for finite population inference from nonprobability samples using auxiliary information from one or multiple probability reference surveys. The package supports estimation with multiple reference surveys, allowing auxiliary information to be combined when no single survey contains all variables relevant to participation. Optional cumulative precalibration can be applied to align weighted totals of shared variables across surveys. Methods are based on the generalized estimating equations framework of Landsman et al. (2026) <doi:10.1002/sim.70403> for correcting participation bias. For a single reference survey, the package implements the raking ratio calibration method and includes the adjusted logistic propensity (ALP) method of Wang, Valliant, and Li (2021) <doi:10.1002/sim.9122>, as well as the Chen-Li-Wu (CLW) method of Chen, Li, and Wu (2020) <doi:10.1080/01621459.2019.1677241>. Analytic variance estimation uses Taylor linearization and accounts for complex sampling designs in the reference surveys via integration with the 'survey' package.