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Articles 1 - 4 of 4
Full-Text Articles in Statistical Methodology
Bayesian Methods For Graphical Models With Neighborhood Selection., Sagnik Bhadury
Bayesian Methods For Graphical Models With Neighborhood Selection., Sagnik Bhadury
Electronic Theses and Dissertations
Graphical models determine associations between variables through the notion of conditional independence. Gaussian graphical models are a widely used class of such models, where the relationships are formalized by non-null entries of the precision matrix. However, in high-dimensional cases, covariance estimates are typically unstable. Moreover, it is natural to expect only a few significant associations to be present in many realistic applications. This necessitates the injection of sparsity techniques into the estimation method. Classical frequentist methods, like GLASSO, use penalization techniques for this purpose. Fully Bayesian methods, on the contrary, are slow because they require iteratively sampling over a quadratic …
Examining The Credibility Of Story-Based Causal Methodologies, Megan E. Kauffmann
Examining The Credibility Of Story-Based Causal Methodologies, Megan E. Kauffmann
Electronic Theses and Dissertations
The purpose of this study was to explore how evaluators justify using story-based methodologies when examining causality. The two primary research questions of the study included: 1) what arguments are made by evaluators to justify the credibility of story-based causal methodologies to evaluation stakeholders; and 2) from the perspective of evaluators, how do contextual factors influence whether story-based causal methodologies are perceived as credible by evaluation stakeholders? A case study was conducted to examine the cases of four evaluators who had experience implementing a story-based methodology in an evaluation. Data collection procedures included two interviews with each participant and a …
Mis-Specification Of Functional Forms In Growth Mixture Modeling: A Monte Carlo Simulation, Richa Ghevarghese
Mis-Specification Of Functional Forms In Growth Mixture Modeling: A Monte Carlo Simulation, Richa Ghevarghese
Electronic Theses and Dissertations
Growth mixture modeling (GMM) is a methodological tool used to represent heterogeneity in longitudinal datasets through the identification of unobserved subgroups following qualitatively and quantitatively distinct trajectories in a population. These growth trajectories or functional forms are informed by the underlying developmental theory, are distinct to each subgroup, and form the core assumptions of the model. Therefore, the accuracy of the assumed functional forms of growth strongly influences substantive research and theories of growth. While there is evidence of mis-specified functional forms of growth in GMM literature, the weight of this violation has been largely overlooked. Current solutions to circumvent …
Application Of An Organizational Evaluation Capacity Assessment In A Multinational Ngo: A Case Study To Support Applied Practice, Ryan James Smyth
Application Of An Organizational Evaluation Capacity Assessment In A Multinational Ngo: A Case Study To Support Applied Practice, Ryan James Smyth
Electronic Theses and Dissertations
As evaluation capacity building (ECB) has rapidly emerged as a practice in human service organizations and as a field of academic inquiry, attention has focused on methods of evaluation capacity building while assessment of organizational evaluation capacity (EC) has lagged behind. To examine the practice of organizational evaluation capacity assessment, this dissertation presents two separate but related studies. In sub-study 1, I present a qualitative evidence synthesis of the research theorizing organizational evaluation capacity models. In sub-study 2, I support the implementation of one of the tools from the evidence-synthesis at a multinational human service organization. I use a concurrent …