"Nonprofit theory predicts nonprofit enterprises will be more trustworthy than for-profit enterprises in the delivery of goods for which quality is difficult to determine because nonprofit enterprises are legally required to reinvest all profits back into the enterprise. Theoretically, consumers...

Source: Dissertation Abstracts International, Volume: 69-03, Section: B, page: 1720.

Source: Dissertation Abstracts International, Volume: 59-10, Section: B, page: 5428.

Source: Dissertation Abstracts International, Volume: 63-10, Section: B, page: 4749.

This thesis examines causal inference related topics involving intermediate variables, and uses Bayesian methodologies to advance analysis capabilities in these areas. First, joint modeling of outcome variables with intermediate variables is considered in the context of birthweight and censored...

The current study aimed to determine the best method for estimating latent variable interactions as a function of the size of the interaction effect, sample size, the loadings of the indicators, the size of the relation between the first-order latent variables, and normality. Data were simulated...

Probabilistic graphical models, by making conditional independence assumptions, can represent complex joint distributions in a factorized form. However, in large problems graphical models often run into two issues. First, in non-treelike graphs, computational issues frustrate exact inference....

In the study of finance, likelihood based or moment based methods are frequently used to estimate parameters for various kinds of models given the sampled return data. While the former method is not robust, the latter one suffers from loss of efficiency and high noise-to-signal ratio in the...

Growth mixture modeling has gained much attention in applied and methodological social science research recently, but the selection of the number of latent classes for such models remains a challenging issue. This problem becomes more serious when one of the key assumptions of this model, proper...