Block What You Can, Except When You Shouldn’t

نویسندگان

چکیده

Several branches of the potential outcome causal inference literature have discussed merits blocking versus complete randomization. Some concluded it can never hurt precision estimates, and some hurt. In this paper, we reconcile these apparently conflicting views, give a more thorough discussion what guarantees no harm, discuss how other aspects blocked design cost, all in terms precision. We different findings are due to sampling models assumptions blocks were formed. also connect ideas common misconceptions, for instance showing that analyzing experiment as if completely randomized, seemingly conservative method, actually backfire cases. Overall, find price, but price is usually small gain be large. It hard go too far wrong with blocking.

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ژورنال

عنوان ژورنال: Journal of Educational and Behavioral Statistics

سال: 2021

ISSN: ['1076-9986', '1935-1054']

DOI: https://doi.org/10.3102/10769986211027240