Response-based multiple imputation method for minimizing the impact of covariate detection limit in logistic regression
Article
Article Title | Response-based multiple imputation method for minimizing the impact of covariate detection limit in logistic regression |
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ERA Journal ID | 791 |
Article Category | Article |
Authors | Hossain, Shahadut, Hoque, Zahirul and Wesolowski, Jacek |
Journal Title | Communications in Statistics: Theory and Methods |
Journal Citation | 50 (2), pp. 371-386 |
Number of Pages | 16 |
Year | 2021 |
Publisher | Taylor & Francis |
Place of Publication | United States |
ISSN | 0361-0926 |
1532-415X | |
Digital Object Identifier (DOI) | https://doi.org/10.1080/03610926.2019.1635699 |
Web Address (URL) | https://www.tandfonline.com/doi/abs/10.1080/03610926.2019.1635699 |
Abstract | Presence of detection limit (DL) in covariates causes inflated bias and inaccurate mean squared error to the estimators of the regression parameters. This paper suggests a response-driven multiple imputation method to correct the deleterious impact introduced by the covariate DL in the estimators of the parameters of simple logistic regression model. The performance of the method has been thoroughly investigated, and found to outperform the existing competing methods. The proposed method is computationally simple and easily implementable by using three existing R libraries. The method is robust to the violation of distributional assumption for the covariate of interest. |
Keywords | Detection limit; left-truncation; logistic regression; multiple lmputation |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 490508. Statistical data science |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | United Arab Emirates University, United Arab Emirates |
Warsaw University of Technology, Poland |
https://research.usq.edu.au/item/z3qz0/response-based-multiple-imputation-method-for-minimizing-the-impact-of-covariate-detection-limit-in-logistic-regression
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