qolef

The variables are as follows:<ul>
<li>id: patients id</li>
<li>y: EF score</li>
<li>time: time in months since randomization</li>
<li>group: placebo (0) or flutamide (1)</li>
<li>perf: baseline performance score</li>
<li>sever: baseline disease severity</li>
<li>t1: indicator variable for month 1</li>
<li>t3: indicator variable for month 3</li>
<li>t6: indicator variable for month 6</li>
<li>yp: most recently observed prior outcome</li>
<li>basey: EF at baseline</li>
<li>g: missingness status ("O"=observed, "D"=dropout, "I"=intermittent missingness)</li>
<li>gp: missingness status in the prior visit ("O"=observed, "D"=dropout, "I"=intermittent missingness, "U"=undefined)</li>
</ul>

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>.

qolef: A data set for Quality of Life Emontional Functioning outcome.

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