Effects of Missing Data Methods in Structural Equation Modeling With Nonnormal Longitudinal Data

By Tacksoo Shin, Mark L. Davison, Jeffrey D. Long. 2009

81 citations recorded by the source corpus.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/2e5086cdfa44a324405f301e96b627c373b238e7

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In Statistics and Probability

1. Rebecca J. Collie

Citations in the corpus

• COVID-19 and Teachers’ Somatic Burden, Stress, and Emotional Exhaustion: Examining the Role of Principal Leadership and Workplace Buoyancy (2021, methodology): “When used in combination with the MLR estimator, FIML has been shown to be appropriate under missing-at-random (MAR) assumptions, in situations of high missing data (<50%), and even in some situations when MAR assumptions have been violated (Enders & Bandalos, 2001; Shin et al., 2009).”