A new information integration framework for complex models with applications to real-world data.
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| Title: | A new information integration framework for complex models with applications to real-world data. |
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| Authors: | Liang J; Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, USA., Falve J; Department of Physical Therapy and Rehabilitation Science, University of Maryland School of Medicine, Baltimore, MD, USA., Chen S; Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, USA.; Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA., McCoy R; Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA.; Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.; University of Maryland Institute for Health Computing, North Bethesda, MD, USA., Chen C; Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA.; University of Maryland Institute for Health Computing, North Bethesda, MD, USA. |
| Source: | Statistical methods in medical research [Stat Methods Med Res] 2026 Jul; Vol. 35 (7), pp. 1366-1381. Date of Electronic Publication: 2026 May 23. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: SAGE Publications Country of Publication: England NLM ID: 9212457 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1477-0334 (Electronic) Linking ISSN: 09622802 NLM ISO Abbreviation: Stat Methods Med Res Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1477-0334 |
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| DOI: | 10.1177/09622802261445563 |
