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The design and analysis of experiments.
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Covariate adjustment in randomization-based causal inference for 2K factorial designs
TL;DR: In this article, a finite-population asymptotic theory for covariate adjustment in randomization-based causal inference for 2 K factorial designs is developed, and both the unadjusted and the covariate-adjusted estimators of the factorial effects are asymPTotically unbiased and normal.
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A Note on Uniformly Best Unbiased Estimators for Variance Components
TL;DR: In this article, a note on Uniformly Best Unbiased Estimators for Variance Components is given. But it does not specify the best unbiased estimator for each component. And it is not available in this paper.
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Effect of increased test‐taking time on test scores by ethnic group, years out of school, and sex
TL;DR: This article investigated the effect of test-taking time on the scores of minority groups on the GRE Aptitude Test and found no significant interaction between ethnic groups and time factors, but no evidence showing subgroup bias has been found.
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Statistical considerations for in vitro research: I — Birth of an idea to collecting data
Michael E. Compton,Carl W. Mize +1 more
TL;DR: This paper focuses on topics to consider when planning experiments and provides examples of several experimental designs that are suitable for plant tissue culture and biotechnology projects.
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Designs for Variance Components Estimation: Past and Present
TL;DR: In this article, a comprehensive coverage of the literature on designs for estimating variance components, and a review of recent applications of such designs in genetics, statistical process control, and quality improvement are discussed.