Local influence for incomplete data models

By Hong-Tu Zhu, Sik-Yum Lee. 2001

214 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/326e3abdf77119bfe61d9ba38002d30c63c5fc3f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

Citations in the corpus

Skew scale mixtures of normal distributions: Properties and estimation (2011, result): “Moreover, studies related to local influence for incomplete data (Zhu and Lee, 2001) can be easily extended from these results which will be reported elsewhere.”
Weighted Generalized Estimating Functions for Longitudinal Response and Covariate Data That Are Missing at Random (2010, background): “…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; Molenberghs and Verbeke 2005).”
Robust statistical modeling using the Birnbaum-Saunders- t distribution applied to insurance (2012, background): “Local influence Under the presence of latent or incomplete data, Zhu and Lee [37] proposed the log-likelihood Q-displacement function adapting the local influence approach to this case; see also [38].”
Perturbation selection and influence measures in local influence analysis (2007, methodology): “Lee and Tang [17] examined local influence in structural equation models.”
Influence analysis in skew-Birnbaum–Saunders regression models and applications (2011, methodology): “Based on the direction of some unit vector d, the normal curvature CfQ,d of ρ(ω) at ω0 can be used to summarize the local behavior of the loglikelihood Q-displacement function proposed by Zhu and Lee [37].”