Imputation of missing values is superior to complete case analysis and the missing-indicator method in multivariable diagnostic research: a clinical example.

By G. V. D. van der Heijden, A. T. Donders, Theo Stijnen, Karel G. M. Moons. Journal of Clinical Epidemiology, 2006

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Comparison of Performance of Data Imputation Methods for Numeric Dataset (2019, methodology): “A study conducted by Geert et al. (2006) found that single imputation method results in too small estimated standard errors, whereas multiple imputation results in correctly estimated standard errors and confidence interval. The study conducted by Penone et al. (2014) evaluates performance of four a”
Multiple Imputation of Missing Data: A Simulation Study on a Binary Response (2013, background): “less than 5% per variable, they may perform well enough for most practical applications in the social sciences and medicine [5,14,15].”