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Rerandomization

Morgan, Kari Lock Balakrishnan, N. ; Everitt, Brian ; Colton, Theodore ; Teugels, Jozef L. ; Piegorsch, Walter ; Ruggeri, Fabrizio

Wiley StatsRef: Statistics Reference Online, 2022, p.1-7

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Título:
Rerandomization
Autor: Morgan, Kari Lock
Balakrishnan, N. ; Everitt, Brian ; Colton, Theodore ; Teugels, Jozef L. ; Piegorsch, Walter ; Ruggeri, Fabrizio
Assuntos: Design of Experiments ; Methods and Theory
É parte de: Wiley StatsRef: Statistics Reference Online, 2022, p.1-7
Descrição: Randomized experiments are the gold standard for estimating causal effects, because randomization balances covariates between the treatment groups in expectation. However, in any particular allocation, covariates may be unbalanced simply by chance, and experiments can be improved by avoiding such imbalances. Rather than to proceed with a treatment allocation known to exhibit covariate imbalance, we can rerandomize, provided the decision rule for whether to rerandomize is objective and specified in advance. Rerandomization involves two steps: (i) specifying a criterion for acceptable covariate balance and then (ii) iterating between randomizing units into treatment groups and checking covariate balance until the specified criterion is met. In addition to providing better covariate balance, when the covariates being balanced are correlated with the outcome, rerandomization increases the precision of the estimated treatment effect. Rerandomization is flexible and can be adapted to a variety of different settings.
Editor: Chichester, UK: John Wiley & Sons, Ltd
Idioma: Inglês

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