Best practices for missing data management in counseling psychology.

By G. Schlomer, Sheri Bauman, Noel A. Card. Journal of counseling and psychology, 2010

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A self-determination theory approach to predicting school achievement over time: the unique role of intrinsic motivation (2014, methodology): “This technique has also been shown to outperform older ad-hoc procedures such as listwise deletion or mean substitution (Schlomer et al., 2010), and several studies have indicated that it yields the least biased and most efficient parameter estimates (Peugh & Enders, 2004).”
The Development and Validation of the Game User Experience Satisfaction Scale (GUESS) (2016, methodology): “The EM method is considered to be most appropriate for non-hypothesis-testing analyses, such as EFA and internal consistency calculations (Enders, 2003; Schlomer, Bauman, & Card, 2010).”
Handling Item-Level Missing Data (2013, background): “The same blurring is present within the paper by Schlomer et al. (2010), who discuss both item- and scale-level missingness but do not make distinctions between them; indeed, results of their analysis, which focuses on very high levels of scale-level missingness in a three-variable model, are…”
The Misunderstood Schema of the Strong Black Woman: Exploring Its Mental Health Consequences and Coping Responses Among African American Women (2020, methodology): “The results suggest the appropriateness of using model-based methods of missing data estimation, namely the full information maximum likelihood (FIML) estimation (Schlomer et al., 2010).”