5 papers · 1 filter
Towards more scientific meta-analyses
Lily H. Zhang, Menelaos Konstantinidis, Marie-Abèle Bind +1
Meta-analysis can be a critical part of the research process, often serving as the primary analysis on which the practitioners, policymakers, and individuals base their decisions.…
Conceptualizing experimental controls using the potential outcomes framework
Kristen B. Hunter, Kristen Koenig, Marie-Abèle Bind
The goal of a well-controlled study is to remove unwanted variation when estimating the causal effect of the intervention of interest. Experiments conducted in the basic sciences f…
Bayesian causal inference for count potential outcomes
Young Lee, Wicher P. Bergsma, Marie-Abele C. Bind
The literature for count modeling provides useful tools to conduct causal inference when outcomes take non-negative integer values. Applied to the potential outcomes framework, we…
Causal Inference for Multiple Treatments using Fractional Factorial Designs
Nicole E. Pashley, Marie-Abele C. Bind
We consider the design and analysis of multi-factor experiments using fractional factorial and incomplete designs within the potential outcome framework. These designs are particul…
Randomization-based Inference for Bernoulli-Trial Experiments and Implications for Observational Studies
Zach Branson, Marie-Abele Bind
We present a randomization-based inferential framework for experiments characterized by a strongly ignorable assignment mechanism where units have independent probabilities of rece…