In Single-Case Designs (SCD), the outcome variable most commonly involves some form of count data. However, statistical analyses and associated effect size (ES) calculations for count outcomes have only recently been proposed. Three recently proposed ES methods for count data are: Nonlinear Bayesian effect size (Rindskopf, 2014), Log Response…

This dissertation is a collection of three papers. The first is a conceptual paper, followed by two data analysis papers. All three papers examine the connection between structural equation models and regression models, and how one may better learn, research and apply structural equation models when structural equation models are thought of as…

We study flexible Bayesian methods that are amenable to a wide range of learning problems involving complex high dimensional data structures, with minimal tuning. We consider parametric and semiparametric Bayesian models, that are applicable to both static and dynamic data, arising from a multitude of areas such as economics, finance and…