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Attention is given to the benefits of using survival analysis as a data analytic technique applicable for employee retention studies.
In a data analytic view, informaticists are familiar with unsupervised clustering analysis and class-label supervised clustering analysis.
From a data analytic standpoint, premature termination will be handled via the use of random regression (RR) models which permit estimation of changes in continuous repeated measures on both a population and subject-specific level, without necessitating last observation carried forward (LOCF) or exclusion of subjects with missing data in the dependent variable.
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