A new technique for handling non-probability samples based on model-assisted kernel weighting
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DOI: 10.1016/j.matcom.2024.08.009
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- Yilin Chen & Pengfei Li & Changbao Wu, 2020. "Doubly Robust Inference With Nonprobability Survey Samples," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(532), pages 2011-2021, December.
- Bart Buelens & Joep Burger & Jan A. van den Brakel, 2018. "Comparing Inference Methods for Non‐probability Samples," International Statistical Review, International Statistical Institute, vol. 86(2), pages 322-343, August.
- Lingxiao Wang & Barry I. Graubard & Hormuzd A. Katki & and Yan Li, 2020. "Improving external validity of epidemiologic cohort analyses: a kernel weighting approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1293-1311, June.
- Jae Kwang Kim & Zhonglei Wang, 2019. "Sampling Techniques for Big Data Analysis," International Statistical Review, International Statistical Institute, vol. 87(S1), pages 177-191, May.
- Luis Castro-Martín & María del Mar Rueda & Ramón Ferri-García & César Hernando-Tamayo, 2021. "On the Use of Gradient Boosting Methods to Improve the Estimation with Data Obtained with Self-Selection Procedures," Mathematics, MDPI, vol. 9(23), pages 1-23, November.
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Keywords
Model-assisted kernel; Kernel weighting; Employment; Confinement period; COVID-19;All these keywords.
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