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Group by: Year | Authors/Creators | Item Type | Full Text
Jump to: 2013 | 2012 | 2011 | 2010 | 2009 | 2006 | 2001
Number of items: 10.

2013

Pantazis, N; Kenward, MG; Touloumi, G; Eurocoord, CascadeCollaboration; (2013) Performance of parametric survival models under non-random interval censoring: A simulation study. Computational statistics & data analysis, 63. pp. 16-30. ISSN 0167-9473 DOI: 10.1016/j.csda.2013.01.014 Full text not available from this repository.

2012

2011

Sotto, C; Beunckens, C; Molenberghs, G; Kenward, MG; (2011) MCMC-based estimation methods for continuous longitudinal data with non-random (non)-monotone missingness. Computational statistics & data analysis, 55 (1). pp. 301-311. ISSN 0167-9473 DOI: 10.1016/j.csda.2010.04.026 Full text not available from this repository.

2010

Molenberghs, G; Kenward, MG; (2010) Semi-parametric marginal models for hierarchical data and their corresponding full models. Computational statistics & data analysis, 54 (2). pp. 585-597. ISSN 0167-9473 DOI: 10.1016/j.csda.2009.09.040 Full text not available from this repository.

White, IR; Daniel, R; Royston, P; (2010) Avoiding bias due to perfect prediction in multiple imputation of incomplete categorical variables. Computational statistics & data analysis, 54 (10). pp. 2267-2275. ISSN 0167-9473 DOI: 10.1016/j.csda.2010.04.005 Full text not available from this repository.

2009

Sepulveda, N; Paulino, CD; Penha-Goncalves, C; (2009) Bayesian analysis of allelic penetrance models for complex binary traits. Computational statistics & data analysis, 53 (4). pp. 1271-1283. ISSN 0167-9473 Full text not available from this repository.

2006

Jansen, I; Hens, N; Molenberghs, G; Aerts, M; Verbeke, G; Kenward, MG; (2006) The nature of sensitivity in monotone missing not at random models. Computational statistics & data analysis, 50 (3). pp. 830-858. ISSN 0167-9473 DOI: 10.1016/j.csda.2004.10.009 Full text not available from this repository.

2001

Molenberghs, G; Verbeke, C; Thijs, H; Lesaffre, E; Kenward, MG; (2001) Influence analysis to assess sensitivity of the dropout process. Computational statistics & data analysis, 37 (1). pp. 93-113. ISSN 0167-9473 Full text not available from this repository.

This list was generated on Sat Apr 29 12:24:47 2017 BST.