Multiple Imputation Confidence Intervals for a Risk Difference With Missing Observations.
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| Názov: | Multiple Imputation Confidence Intervals for a Risk Difference With Missing Observations. |
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| Autori: | Lee CH; Department of Statistics, National Cheng Kung University, Tainan, Taiwan. |
| Zdroj: | Statistics in medicine [Stat Med] 2025 Jun; Vol. 44 (13-14), pp. e70136. |
| Spôsob vydávania: | Journal Article |
| Jazyk: | English |
| Informácie o časopise: | Publisher: Wiley Country of Publication: England NLM ID: 8215016 Publication Model: Print Cited Medium: Internet ISSN: 1097-0258 (Electronic) Linking ISSN: 02776715 NLM ISO Abbreviation: Stat Med Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Chichester ; New York : Wiley, c1982- |
| Výrazy zo slovníka MeSH: | Confidence Intervals* , Risk*, Binomial Distribution ; Computer Simulation ; Data Interpretation, Statistical ; Models, Statistical ; Poisson Distribution |
| Abstrakt: | Confidence interval estimation for a risk difference is commonly used in various applications. The method of variance estimates recovery (MOVER) is a useful method for constructing the confidence interval of the risk difference. The confidence interval estimation with incomplete data has been widely studied in recent years, as missing values can occur during data collection. In this study, for the Poisson and binomial distributions, we propose proper multiple imputation procedures for the MOVER to estimate the confidence intervals for the risk difference, not only for missing at random but also for missing not at random. A simulation study shows that the coverage probabilities of the proposed intervals are closer to the nominal level than those of existing intervals, particularly when the true parameters are near the boundaries. These multiple imputation confidence intervals are illustrated with real data examples. (© 2025 John Wiley & Sons Ltd.) |
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| Grant Information: | 111-2118-M-194-004-MY2 National Science and Technology Council; 113-2118-M-006-008- National Science and Technology Council |
| Contributed Indexing: | Keywords: Poisson distribution; binomial distribution; coverage probability; incomplete data; missing data; missing not at random |
| Entry Date(s): | Date Created: 20250610 Date Completed: 20250610 Latest Revision: 20250612 |
| Update Code: | 20250612 |
| DOI: | 10.1002/sim.70136 |
| PMID: | 40493567 |
| Databáza: | MEDLINE |
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Nájsť tento článok vo Web of Science | Abstrakt: | Confidence interval estimation for a risk difference is commonly used in various applications. The method of variance estimates recovery (MOVER) is a useful method for constructing the confidence interval of the risk difference. The confidence interval estimation with incomplete data has been widely studied in recent years, as missing values can occur during data collection. In this study, for the Poisson and binomial distributions, we propose proper multiple imputation procedures for the MOVER to estimate the confidence intervals for the risk difference, not only for missing at random but also for missing not at random. A simulation study shows that the coverage probabilities of the proposed intervals are closer to the nominal level than those of existing intervals, particularly when the true parameters are near the boundaries. These multiple imputation confidence intervals are illustrated with real data examples.<br /> (© 2025 John Wiley & Sons Ltd.) |
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| ISSN: | 1097-0258 |
| DOI: | 10.1002/sim.70136 |