[Forum SIS] Avviso di seminario - Prof. Li-Chun Zhang @ unipg

[Maria Giovanna Ranalli]

.: Li-Chun Zhang, University of Southampton, Statistics Norway & Universitetet i Oslo :.
.: Simple regression methods for secondary analysis of datasets that cannot be linked without errors :.

Giovedì 22 Novembre, ore 13
Dipartimento di Economia, Aula 101
Via Pascoli, 20 - Perugia
Università degli Studi di Perugia

.: Abstract :.

Unless a unique identifier exists for this purpose, linkage of separate datasets will generate errors that can cause bias of the subsequent analysis, if the linked data are treated as if they were truly observed. In this work we take on the perspective of secondary analysts, who we assume to neither have full access to the linkage key variables nor the details or tools of the actual linkage procedure, but at most are only provided with some non-disclosive linkage comparison data about the record linkage precision or how the records compare to each other. We discuss several existing approaches to statistical analysis, and their respective theoretical and practical difficulties. These include the maximum likelihood estimation, the frequentist approach to regression adjustment, and some Bayesian approaches that have been proposed.

Focusing on linear regression as the case-in-point, we develop a simple method of Pseudo OLS for linkage-data regression, where the analyst is only given the linked dataset, but not any of the unlinked records. We do not assume that the true matches are confined to within the units associated with the linked dataset, nor that the linkage error probability is a constant for different units. Moreover, we develop a diagnostic test for the assumption of non-informative linkage errors (NILE), which is needed for all the existing methods of linkage-error adjustment. Our approach will be illustrated by simulation and application to real data. 

Questa iniziativa rientra nel ciclo di seminari organizzato per il Dottorato in Economia ed è aperta a tutti gli interessati.

Cordialmente

M. Giovanna Ranalli, PhD

~ Associate Professor of Statistics
~ Department of Political Science
~ University of Perugia (Italy) 

~ Tel +39 075 5855241
~ Fax +39 075 5855950
~ http://www.stat.unipg.it/~giovanna/ <http://www.stat.unipg.it/~giovanna/>
~ http://www.sp.unipg.it/surwey/ <http://www.sp.unipg.it/surwey/>
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