isni

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.

Last 30 days

This package has been downloaded 224 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 10 times.

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Last 365 days

This package has been downloaded 3,652 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 43 downloads.

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