Sensitivity analysis for incomplete contingency tables: the Slovenian plebiscite case
By Geert Molenberghs, Michael G. Kenward, Els Goetghebeur. 2001
129 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/5e7b4dfa391027637a91aa864e178f2a25c0a3c3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Geert Molenberghs
- Michael G. Kenward
- Caroline Beunckens
- Cristina Sotto
- Geert Verbeke
- Herbert Thijs
- Richard J. Cook
- Grace Y. Yi
In Statistics and Probability
- Geert Molenberghs
- Caroline Beunckens
- Michael G. Kenward
- Cristina Sotto
- Geert Verbeke
- Baojiang Chen
- Richard J. Cook
- Grace Y. Yi
Citations in the corpus
- Every missingness not at random model has a missingness at random counterpart with equal fit (2008, methodology): “In Section 5 we apply the ideas that are developed to data from the Slovenian public opinion survey, which have been analysed before by Rubin et al. (1995) and Molenberghs et al. (2001).”
- A local influence approach to sensitivity analysis of incomplete longitudinal ordinal data (2001, background): “Several authors have suggested various types of sensitivity analyses to address this issue (Molenberghs et al. 2001; Scharfstein et al., 1999; Verbeke et al., 2001).”
- Weighted Generalized Estimating Functions for Longitudinal Response and Covariate Data That Are Missing at Random (2010, background): “…proposed using global and local influence tools for sensitivity analyses in missing-data contexts (e.g., Kenward 1998; Verbeke and Molenberghs 2000; Molenberghs, Kenward, and Goetghebeur 2001; Van Steen, Molenberghs, and Thjis 2001; Verbeke et al. 2001; Zhu and Lee 2001; Jansen et al. 2003;…”