isni:Index of Local Sensitivity to Nonignorability
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
mixed-effects models for continuous and binary
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
<https://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>.
