Quantifying bias due to missing data in quality of life surveys of advanced-stage cancer patients
Author:
Publisher
Springer Science and Business Media LLC
Subject
Public Health, Environmental and Occupational Health
Link
https://link.springer.com/content/pdf/10.1007/s11136-023-03588-7.pdf
Reference34 articles.
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2. Groenwold, R. H. H., & Dekkers, O. M. (2020). Missing data: The impact of what is not there. European Journal of Endocrinology, 183(4), E7–E9. https://doi.org/10.1530/EJE-20-0732
3. Little, R. J. A., & Rubin, D. B. (2002). Statistical analysis with missing data. In Wiley series in probability and statistics (2nd ed.). Wiley. https://doi.org/10.1002/9781119013563
4. Pugh, S. L., Brown, P. D., & Enserro, D. (2021). Missing repeated measures data in clinical trials. Neuro-Oncology Practice, 9(1), 35–42. https://doi.org/10.1093/nop/npab043
5. Mohan, K., & Pearl, J. (2021). Graphical models for processing missing data. Journal of the American Statistical Association, 116(534), 1023–1037. https://doi.org/10.1080/01621459.2021.1874961
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