Clay weekly context brief for the Statistics category (ISO week 2026-W36).

Clay tracks publications from the Statistics feed list. Below are recent items from this category, each with its source and a short description of what the publication covers when one is available in the source feed.

Recent publications:
1. Target Trial Emulation with the R Package TTE: A Tutorial and Methodological Guide
   Source: stat.AP (Applications)
   Link: https://arxiv.org/abs/2608.01625
   Target trial emulation structures observational causal analyses around the protocol of an ideal randomized trial.
2. Two-stage Adaptive Design Cluster Randomised Trials
   Source: stat.AP (Applications)
   Link: https://arxiv.org/abs/2603.05561
   Adaptive sample size re-estimation, early stopping, and trial re-design at interim analyses can reduce expected sample sizes in randomised trials.
3. Biases in Expected Goals Models Confound Finishing Ability
   Source: stat.AP (Applications)
   Link: https://arxiv.org/abs/2401.09940
   Expected Goals (xG) has emerged as a popular tool for evaluating finishing skill in soccer analytics.
4. A Deep Zero-Inflated Model of North Atlantic Right Whale Presence To Support Blue Economy Management in the U.S. East Coast
   Source: stat.AP (Applications)
   Link: https://arxiv.org/abs/2606.14403
   Effective modeling of endangered marine mammal species, such as the North Atlantic Right Whale, is critical for balancing marine conservation with the growing blue economy.
5. Optimal Adversarial Testing: Extracting Honest Test Results from Dishonest Test Takers
   Source: stat.AP (Applications)
   Link: https://arxiv.org/abs/2608.28362
   In applications, it is often required to test objects or people to determine their qualities in terms of certain metrics.
6. Response Propensity Estimation and Cross-Fitting
   Source: stat.AP (Applications)
   Link: https://arxiv.org/abs/2608.28324
   This paper investigates whether five fold cross fitting improves nonresponse adjustment in survey estimation when flexible machine learning methods are used to estimate response propensities.

Sources in this brief: stat.AP (Applications).
Selected 6 of 6 available items for this weekly brief.