The current version provides functions to compute, print and summarize the Index of Sensitivity to Nonignorability (ISNI) in the generalized linear model for independent data, and in the marginal multivariate Gaussian model and the linear mixed model for longitudinal/clustered data. It allows for arbitrary patterns of missingness in the regression outcomes caused by dropout and/or intermittent missingness. One can compute the sensitivity index without estimating any nonignorable models or positing specific magnitude of nonignorability. Thus ISNI provides a simple quantitative assessment of how robust the standard estimates assuming missing at random is with respect to the assumption of ignorability. For a tutorial, download at <http://huixie.people.uic.edu/Research/ISNI_R_tutorial.pdf>. For more details, see Troxel Ma and Heitjan (2004) and Xie and Heitjan (2004) <doi:10.1191/1740774504cn005oa> and Ma Troxel and Heitjan (2005) <doi:10.1002/sim.2107> and Xie (2008) <doi:10.1002/sim.3117> and Xie (2012) <doi:10.1016/j.csda.2010.11.021> and Xie and Qian (2012) <doi:10.1002/jae.1157>.
Package details 


Author  Hui Xie <[email protected]>, Weihua Gao, Baodong Xing, Daniel Heitjan, Donald Hedeker, Chengbo Yuan 
Maintainer  Hui Xie <[email protected]> 
License  GPL2 
Version  0.4 
Package repository  View on CRAN 
Installation 
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