Comment: The Design and Analysis of Gold Standard Randomized Experiments

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Optimal a priori balance in the design of controlled experiments (2013, background): “the common statistical maxim “block what you can, randomize what you cannot” attributed to George Box and in the words of such individuals as James Heckman (“Randomization is a metaphor and not an ideal or ‘gold standard”’ [2]) and Donald Rubin (“For gold standard answers, complete randomization may”
The Validity and Precision of the Comparative Interrupted Time-Series Design (2016, methodology): “To account for any small imbalances, the RCT treatment estimates referenced below come from fully adjusted models that include all pretest and demographic covariates (Rubin, 2008).”
Why Propensity Scores Should Not Be Used for Matching (2019, background): “This is the reason scholars who study matching uniformly recommend that Y should not be consulted during the matching process (Rubin, 2008b).”
When second best is good enough: a comparison between a true experiment and a regression discontinuity quasi-experiment (2010, background): “At the same time, however, comparisons between randomized experiments and the alternatives can raise a number of subtle issues (Hill, 2008; Little et al., 2008; Rubin, 2008).”