Michael Sklar

Michael Sklar
Stanford University | SU · Department of Statistics

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5
Publications
401
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27
Citations

Publications

Publications (5)
Article
We present an optimized rerandomization design procedure for a non-sequential treatment-control experiment. Randomized experiments are the gold standard for finding causal effects in nature. But sometimes random assignments result in unequal partitions of the treatment and control group visibly seen as imbalance in observed covariates. There can ad...
Preprint
We consider the problem of evaluating designs for a two-arm randomized experiment with the criterion being the power of the randomization test for the one-sided null hypothesis. Our evaluation assumes a response that is linear in one observed covariate, an unobserved component and an additive treatment effect where the only randomness comes from th...
Article
There is a long debate in experimental design between the classic randomization design of Fisher, Yates, Kempthorne, Cochran and those who advocate deterministic assignments based on notions of optimality. In non-sequential trials comparing treatment and control, covariate measurements for each subject are known in advance, and subjects can be divi...
Preprint
We present an optimized rerandomization design procedure for a non-sequential treatment-control experiment. Randomized experiments are the gold standard for finding causal effects in nature. But sometimes random assignments result in unequal partitions of the treatment and control group, visibly seen as imbalanced observed covariates, increasing es...
Article
Full-text available
We study a regression problem where for some part of the data we observe both the label variable ($Y$) and the predictors (${\bf X}$), while for other part of the data only the predictors are given. Such a problem arises, for example, when observations of the label variable are costly and may require a skilled human agent. If the conditional expect...

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