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Balancing Bias and Variance in Network Experiments: When Should you Cluster?by@escholar
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Balancing Bias and Variance in Network Experiments: When Should you Cluster?

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Delve into the decision-making process of choosing between cluster and Bernoulli designs in experiments. This paper thoroughly explores worst-case bias and variance, offering valuable insights into the optimal use of cluster designs. Uncover scenarios where cluster designs outperform Bernoulli designs and gain practical implications for experimental bias considerations. Discover a rule of thumb for making informed decisions, especially in the presence of equally sized clusters, ensuring your experimental design aligns with your research goals.
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EScholar: Electronic Academic Papers for Scholars HackerNoon profile picture
EScholar: Electronic Academic Papers for Scholars

EScholar: Electronic Academic Papers for Scholars

@escholar

We publish the best academic work (that's too often lost to peer reviews & the TA's desk) to the global tech community

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EScholar: Electronic Academic Papers for Scholars HackerNoon profile picture
EScholar: Electronic Academic Papers for Scholars@escholar
We publish the best academic work (that's too often lost to peer reviews & the TA's desk) to the global tech community

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