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  "Title": "Inference Based on Non-Probability Samples",
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  "Authors@R": "c(person(given = \"Łukasz\",\nfamily = \"Chrostowski\",\nrole = c(\"aut\", \"ctb\"),\nemail = \"lukaszchrostowski6@gmail.com\"),\nperson(given = \"Maciej\",\nfamily = \"Beręsewicz\",\nrole = c(\"aut\", \"cre\"),\nemail = \"maciej.beresewicz@ue.poznan.pl\",\ncomment = c(ORCID = \"0000-0002-8281-4301\")),\nperson(given = \"Piotr\",\nfamily = \"Chlebicki\",\nrole = c(\"aut\", \"ctb\"),\nemail = \"piotrek.pecet@gmail.com\",\ncomment = c(ORCID = \"0009-0006-4867-7434\")))",
  "Description": "Statistical inference with non-probability samples when\nauxiliary information from external sources such as probability\nsamples or population totals or means is available. The package\nimplements various methods such as inverse probability\n(propensity score) weighting, mass imputation and doubly robust\napproach. Details can be found in: Chen et al. (2020)\n<doi:10.1080/01621459.2019.1677241>, Yang et al. (2020)\n<doi:10.1111/rssb.12354>, Kim et al. (2021)\n<doi:10.1111/rssa.12696>, Yang et al. (2021)\n<https://www150.statcan.gc.ca/n1/pub/12-001-x/2021001/article/00004-eng.htm>\nand Wu (2022)\n<https://www150.statcan.gc.ca/n1/pub/12-001-x/2022002/article/00002-eng.htm>.\nFor details on the package and its functionalities see\n<doi:10.48550/arXiv.2504.04255>.",
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