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Abstract
This dissertation overcomes several missing data problems in ex-post survey harmonization. Although ex-post survey harmonization projects have become more common in the social sciences in recent years, methodological research on this topic is still relatively rare. The dissertation's main body consists of four chapters, each of which presents a study exploring solutions for missing data problems not only in ex-post survey harmonization but also in related research fields. The study presented in Chapter 2 deals with multiple imputation approaches for discrete-time survival analysis. Chapter 3 presents a study examining multiple imputation approaches to handling systematically missing partner variables. The study presented in Chapter 4 is on the topic of sensitivity analysis in the case of unobserved confounders. And finally, the study in Chapter 5 is on the topic of weighting pooled survey data. The last chapter concludes the dissertation with a discussion of the results, scientific contributions, and limitations of the aforementioned studies, plus a broader outlook on the issue of study heterogeneity.
Dokumententyp: | Hochschulschrift (Dissertation) |
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Fakultät: | Mathematik, Informatik und Statistik > Statistik > Lehrstühle/Arbeitsgruppen > Lehrstuhl für Statistik und ihre Anwendungen in Wirtschafts- und Sozialwissenschaften |
Themengebiete: | 300 Sozialwissenschaften > 310 Statistiken |
URN: | urn:nbn:de:bvb:19-epub-77414-0 |
Ort: | Mannheim |
Sprache: | Englisch |
Dokumenten ID: | 77414 |
Datum der Veröffentlichung auf Open Access LMU: | 14. Sep. 2021, 13:34 |
Letzte Änderungen: | 18. Jul. 2022, 07:49 |