دورية أكاديمية
Categorical linkage-data analysis.
| العنوان: | Categorical linkage-data analysis. |
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| المؤلفون: | Zhang LC; Department of Social Statistics and Demography, University of Southampton, Southampton, UK., Tuoto T; Department of Social Statistics and Demography, Istituto Nazionale di Statistica, Rome, Italy. |
| المصدر: | Statistics in medicine [Stat Med] 2024 Aug 15; Vol. 43 (18), pp. 3463-3483. Date of Electronic Publication: 2024 Jun 10. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Wiley Country of Publication: England NLM ID: 8215016 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-0258 (Electronic) Linking ISSN: 02776715 NLM ISO Abbreviation: Stat Med Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: Chichester ; New York : Wiley, c1982- |
| مواضيع طبية MeSH: | Medical Record Linkage*/methods , Models, Statistical* , Computer Simulation*, Humans ; Data Interpretation, Statistical ; Probability |
| مستخلص: | Analysis of integrated data often requires record linkage in order to join together the data residing in separate sources. In case linkage errors cannot be avoided, due to the lack a unique identity key that can be used to link the records unequivocally, standard statistical techniques may produce misleading inference if the linked data are treated as if they were true observations. In this paper, we propose methods for categorical data analysis based on linked data that are not prepared by the analyst, such that neither the match-key variables nor the unlinked records are available. The adjustment is based on the proportion of false links in the linked file and our approach allows the probabilities of correct linkage to vary across the records without requiring that one is able to estimate this probability for each individual record. It accommodates also the general situation where unmatched records that cannot possibly be correctly linked exist in all the sources. The proposed methods are studied by simulation and applied to real data. (© 2024 The Author(s). Statistics in Medicine published by John Wiley & Sons Ltd.) |
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| فهرسة مساهمة: | Keywords: analysis of contingency table; heterogeneous linkage error; incomplete match space; linkage data structure; logistic regression; secondary analysis |
| تواريخ الأحداث: | Date Created: 20240610 Date Completed: 20240716 Latest Revision: 20240716 |
| رمز التحديث: | 20240716 |
| DOI: | 10.1002/sim.10134 |
| PMID: | 38853711 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1097-0258 |
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| DOI: | 10.1002/sim.10134 |