The Impact of Missing Data on Sample Reliability Estimates: Implications for Reliability Reporting Practices

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A Two-Stage Approach to Missing Data: Theory and Application to Auxiliary Variables (2009, methodology): “the parameter estimates and the model chi-square, will be incorrect (Enders & Peugh, 2004; Graham, 2003). The reason for this is that the input matrix is treated as if it were obtained from complete data, so that the uncertainty associated with missing data is never incorporated into the standard er”
Estimation of Item Response Theory Parameters in the Presence of Missing Data (2008, methodology): “Prior simulation-based research in which the EM algorithm has been used to impute missing values for categorical data were either done with polytomous responses (5 levels) based on a normally distributed continuum and with a symmetric ordinal distribution (Enders, 2004) or with 5 level polytomous da”
Spirituality in the Workplace: Theory and Measurement (2011, methodology): “Assuming data were missing at random, we used ExpectationMaximization algorithm to impute missing values (Allison, 2003; Enders, 2001, 2003, 2004; Enders & Peugh, 2004).”