A Review of Methods for Missing Data

By Terri D. Pigott. 2001

714 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/bef9f0acaacb61e73ea079b1df033d4e7f5e5056

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Citations in the corpus

Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series (2016, background): “While a long and rich literature addresses pattern recognition with missing data (Cohen and Cohen, 1975; Allison, 2001), most of this literature addresses ﬁxed-length feature vectors, as indicated by reviews of the literature from Garc´ıa-Laencina et al. (2010) and Pigott (2001).”
Best practices for missing data management in counseling psychology. (2010, methodology): “In this method, the maximum amount of available data is retained, and so this method is sometimes referred to as available case analysis (Pigott, 2001).”
Modeling Missing Data in Clinical Time Series with RNNs (2016, background): “While a long and rich literature addresses pattern recognition with missing data (Cohen and Cohen, 1975; Allison, 2001), most of this literature addresses fixed-length feature vectors (Garćıa-Laencina et al., 2010; Pigott, 2001).”
Self-Esteem, Self-Efficacy, and Social Connectedness as Mediators of the Relationship Between Volunteering and Well-Being (2012, background): “The loss of some statistical power was deemed acceptable given the assumption that MCAR status would lead to unbiased parameter estimates (Howell, 2008; Pigott, 2001).”
Meta-Analysis of the Effects of Early Education Interventions on Cognitive and Social Development (2010, methodology): “As noted by Pigott (2001), mean substitution and pairwise deletion methods “provide problematic estimates in almost all instances” (p. 380).”
Future orientation and attitudes mediate career adaptability and decidedness (2016, methodology): “Therefore, missing data replacement was performed using person mean replacement, as this method has been suggested to preserve the sample size (Pigott, 2001).”
Impacts of the COVID-19 Pandemic on Life of Higher Education Students: A Global Perspective (2020, methodology): “With the assumption of “missing completely at random”, meaning that the complete cases are a random sample of the originally identified set of cases, a complete case approach is the most common method for handling missing data in many fields of research, including educational and epidemiologic resea”