<p>A dataset from a survey of sexual behavior</p>

datasets

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 more details, see Troxel Ma and Heitjan (2004) and Xie and Heijan (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>.

Hui Xie

isni

Index of Sensitivity to Nonignorability

r99 function

<p>A data frame with 6136 rows and 5 variables</p>

r99: Dataset for a survey of sexual behavior

Description

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Details