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Judging scholarly posters creates a challenge to assign the judgesefficiently. If there are many posters and few reviews per judge, the commonlyused Balanced Incomplete Block Design is not a feasible option. An additionalchallenge is an unknown number of judges before the event. We propose twoconnected near-balanced incomplete block designs that both satisfy therequirements of our setting: one that generates a connected assignment andbalances the treatments and another one that further balances pairs oftreatments. We describe both fixed and random effects models to estimate thepopulation marginal means of the poster scores and rationalize the use of therandom effects model. We evaluate the estimation accuracy and efficiency,especially the winning chance of the truly best posters, of the two designs incomparison with a random assignment via simulation studies. The two proposeddesigns both demonstrate accuracy and efficiency gains over the randomassignment.

Near-Balanced Incomplete Block Designs with An Application to Poster Competitions