This article is concerned with the study of statistical power in agent-based modeling (ABM).
After an overview of classic statistics theory on how to interpret Type-II error (whose …

Preventing adverse health outcomes is complex due to the multi-level contexts and social
systems in which these phenomena occur. To capture both the systemic effects, local …

There are two major limitations to the potential of computational models in ecology for
producing general insights: their design is path‐dependent, reflecting different underlying …

Verification and validation are two important aspects of model building. Verification and
validation compare models with observations and descriptions of the problem modelled …

* Abstract An update to Volker Grimm and colleagues' Overview, Design concepts and
Details (ODD) protocol for documenting individual and agent based models (I/ABM) has …

High-fidelity models are increasingly used to predict, and guide decision making. Prior work
has emphasized the importance of replication in ensuring reliable modeling, and has …

Despite the critical role that replication plays in the advancement of science, its presence in
modelling literature is rare. To encourage others to conduct replication and report success …

Formalised models are simplified representations of empirical phenomena that help to
abstract away essential mechanisms from details and contexts. Although (mathematical or …

Using the agent-based model of Miller et al.(2012), which depicts how different types of
individuals' memory affect the formation and performance of organizational routines, we …

Computational models of complex systems are usually elaborate and sensitive to
implementation details, characteristics which often affect their verification and validation …