Dealing With Missing Data in Developmental Research

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The Development and Validation of a Measure of Student Attitudes Toward Science, Technology, Engineering, and Math (S-STEM) (2015, methodology): “For surveys with missing data, descriptive analysis led to the conclusion that the data should be assumed to be missing at random (MAR; Enders, 2013).”
An Examination of the Efficacy of Insights in Enhancing the Academic and Behavioral Development of Children in Early Grades. (2014, positive): “2 (Enders, 2013).”
A journey around alpha and omega to estimate internal consistency reliability (2017, background): “The details surpass the objectives of this paper and can be found in the methodological literature (e.g., Enders, 2010, 2013; Graham, 2009), but an outline will be presented here.”
Early development of electrophysiological activity: contribution of periodic and aperiodic components of the EEG signal (2022, methodology): “As the attrition rate in developmental studies is high and missing data might bias the results, we employed maximum likelihood estimation in the analysis in children who came to at least two sessions (Enders, 2013; Graham, 2009; Matta et al., 2018).”