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Harnessing Machine Learning to Address High Levels of Missing Data in Cross-National Studies: From Bias to Precision in Public Service Research

Leizhen Zang & Feng Xiong

Journal of Comparative Policy Analysis: research and practice2025https://doi.org/10.1080/13876988.2025.2478930article
AJG 1ABDC B
Weight
0.44

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3 citations

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https://doi.org/https://doi.org/10.1080/13876988.2025.2478930

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@article{leizhen2025,
  title        = {{Harnessing Machine Learning to Address High Levels of Missing Data in Cross-National Studies: From Bias to Precision in Public Service Research}},
  author       = {Leizhen Zang & Feng Xiong},
  journal      = {Journal of Comparative Policy Analysis: research and practice},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1080/13876988.2025.2478930},
}

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Harnessing Machine Learning to Address High Levels of Missing Data in Cross-National Studies: From Bias to Precision in Public Service Research

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Evidence weight

0.44

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.32 × 0.4 = 0.13
M · momentum0.57 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.