For randomized trials that use text as an outcome, traditional approaches for assessing treatment impact require that each document first be manually coded for constructs of interest by trained human raters. This process, the current standard, is both time-consuming and limiting: even the largest human coding efforts are typically constrained to…

It is not always clear how to adjust for control data in causal inference, balancing the goals of reducing bias and variance. We show how, in a setting with repeated experiments, Bayesian hierarchical modeling yields an adaptive procedure that uses the data to determine how much adjustment to perform. The result is a novel analysis with increased…

The study takes an in-depth examination of the extent to which the availability of resources relates to the efficiency of the school system within the framework of the implementation of competency-based teaching approaches in Cameroon. The study employed a mix of probability sampling approaches, namely simple, cluster and stratified random…