5 citations · 12 across the 9 of their papers we have counts for
9 papers
Estimation of Causal Effects Under K-Nearest Neighbors Interference
Samirah Alzubaidi, Michael J. Higgins
Considerable recent work has focused on methods for analyzing experiments which exhibit treatment interference -- that is, when the treatment status of one unit may affect the resp…
Detecting Treatment Interference under the K-Nearest-Neighbors Interference Model
Samirah H. Alzubaidi, Michael J. Higgins
We propose a model of treatment interference where the response of a unit depends only on its treatment status and the statuses of units within its K-neighborhood. Current methods…
The Benefits of Probability-Proportional-to-Size Sampling in Cluster-Randomized Experiments
Yeng Xiong, Michael J. Higgins
In a cluster-randomized experiment, treatment is assigned to clusters of individual units of interest--households, classrooms, villages, etc.--instead of the units themselves. The…
A new method for quantifying network cyclic structure to improve community detection
Behnaz Moradi-Jamei, Heman Shakeri, Pietro Poggi-Corradini +1
A distinguishing property of communities in networks is that cycles are more prevalent within communities than across communities. Thus, the detection of these communities may be a…
Hybridized Threshold Clustering for Massive Data
Jianmei Luo, ChandraVyas Annakula, Aruna Sai Kannamareddy +3
As the size of datasets become massive, many commonly-used clustering algorithms (for example, -means or hierarchical agglomerative clustering (HAC) require prohibitive comp…
From one environment to many: The problem of replicability of statistical inferences
James J. Higgins, Michael J. Higgins, Jinguang Lin
Among plausible causes for replicability failure, one that has not received sufficient attention is the environment in which the research is conducted. Consisting of the population…