Weighting for item non‐response in attitude scales by using latent variable models with covariates

By Irini Moustaki, M. Knott. 2000

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Rebutting Existing Misconceptions About Multiple Imputation as a Method for Handling Missing Data (2019, methodology): “It should be noted that methods for modeling NMAR have been proposed as well (e.g., Fay, 1986; Galimard, Chevret, Protopopescu, & Resche-Rigon, 2016; Heckman, 1976; Moustaki & Knott, 2000).”
Dealing With Omitted and Not-Reached Items in Competence Tests (2014, background): “Based on work by Moustaki and Knott (2000) and O’Muircheartaigh and Moustaki (1999), Holman and Glas (2005) proposed three models accounting for omitted responses.”
Modeling Nonignorable Missing Data in Speeded Tests (2008, background): “Several authors show that this approach can reduce bias caused by ignoring nonignorable missing data (Holman & Glas, 2005; Moustaki & Knott, 2000; Moustaki & O’Muircheartaigh, 2000; O’Muircheartaigh & Moustaki, 1999).”
Modeling Nonignorable Missing Data with Item Response Theory (IRT). Research Report. ETS RR-10-11. (2010, unknown): “The person estimators of θ can be used to compute weights for each observation (Moustaki & Knott, 2000).”