{ "_id": "6a4d362d088975274b3ce6ce", "Package": "nonprobsampling", "Type": "Package", "Title": "Inference for Nonprobability Samples Using Multiple Reference\nSurveys", "Version": "0.1.0", "Authors@R": "c(\nperson(given = \"Jiakun\",\nfamily = \"Lin\",\nemail = \"jiak.lin@alumni.utoronto.ca\",\nrole = c(\"aut\", \"cre\")),\nperson(given = \"Victoria\",\nfamily = \"Landsman\",\nrole = \"aut\"),\nperson(given = \"Aya A.\",\nfamily = \"Mitani\",\nrole = \"aut\")\n)", "Description": "Provides pseudo-weighted estimates of means and\nprevalences for finite population inference from nonprobability\nsamples using auxiliary information from one or multiple\nprobability reference surveys. The package supports estimation\nwith multiple reference surveys, allowing auxiliary information\nto be combined when no single survey contains all variables\nrelevant to participation. Optional cumulative precalibration\ncan be applied to align weighted totals of shared variables\nacross surveys. Methods are based on the generalized estimating\nequations framework of Landsman et al. (2026)\n for correcting participation bias. 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