2018 January

January, 20 2018 David Steinberg One of the simplest methods for two-group classification is naïve Bayes, in which predictors are treated as though they provide independent information. Traditional event models underlying naive Bayes classifiers assume probability distributions that are not appropriate for binary data generated by human behavior. This paper develops a new event model, based on a somewhat forgotten distribution created by K.T. Wallenius more than 50 years ago. The authors show that it

January, 20 2018 David Steinberg This paper addresses a classical problem in causal inference: matching, where treatment units need to be matched to control units. Some of the main challenges in developing matching methods arise from the tension among (i) inclusion of as many covariates as possible in defining the matched groups, (ii) having matched groups with enough treated and control units for a valid estimate of Average Treatment Effect (ATE) in each group, and