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Articles 1 - 7 of 7
Full-Text Articles in Statistical Methodology
Variational Bayes Estimation Of Discrete-Margined Copula Models With Application To Ime Series, Ruben Loaiza-Maya, Michael S. Smith
Variational Bayes Estimation Of Discrete-Margined Copula Models With Application To Ime Series, Ruben Loaiza-Maya, Michael S. Smith
Michael Stanley Smith
A Cross-Sectional Exploration Of Household Financial Reactions And Homebuyer Awareness Of Registered Sex Offenders In A Rural, Suburban, And Urban County., John Charles Navarro
A Cross-Sectional Exploration Of Household Financial Reactions And Homebuyer Awareness Of Registered Sex Offenders In A Rural, Suburban, And Urban County., John Charles Navarro
Electronic Theses and Dissertations
As stigmatized persons, registered sex offenders betoken instability in communities. Depressed home sale values are associated with the presence of registered sex offenders even though the public is largely unaware of the presence of registered sex offenders. Using a spatial multilevel approach, the current study examines the role registered sex offenders influence sale values of homes sold in 2015 for three U.S. counties (rural, suburban, and urban) located in Illinois and Kentucky within the social disorganization framework. Homebuyers were surveyed to examine whether awareness of local registered sex offenders and the homebuyer’s community type operate as moderators between home selling …
Marketing The Mountain State: A Large N Study Of User Engagement On Twitter, Kirk Richardson
Marketing The Mountain State: A Large N Study Of User Engagement On Twitter, Kirk Richardson
Capstone Projects – Politics and Government
Much of the evolving research on the use of social media in destination marketing emphasizes how information diffusion influences the reputational image of place. The present study uses Twitter data to focus on the relative differences in user engagement across discrete account types. Specifically, this is done to examine how the official destination marketing organization of Montana—the Montana Office of Tourism (MTOT)—performs relative to other account types. Several regression analyses conducted on Twitter data associated with an ongoing MTOT place branding campaign reveal that tweets sent from ‘official’ accounts are more likely to be retweeted, and are estimated to receive …
Incorporating Place And Space: A Hierarchical Spatial Approach To Exploring Preventable Congestive Heart Failure Hospitalizations In New York City, Rachael Weiss Riley
Incorporating Place And Space: A Hierarchical Spatial Approach To Exploring Preventable Congestive Heart Failure Hospitalizations In New York City, Rachael Weiss Riley
Dissertations and Theses
Background: Faced with rising medical care costs, increasing prevalence, and widening health disparities, preventing congestive heart failure (CHF) hospitalizations is a central public health concern. Despite evidence of geographical clustering in preventable CHF admissions, there is a lack of research designed to examine spatial patterning of CHF and the local area neighborhood determinants that contribute to this variability. This study sought to assess and evaluate the importance of both space and place in analyzing preventable CHF hospitalizations and readmissions by applying appropriate statistical techniques, clarifying the assumption inherent in each method, and interpreting the findings within the context of existing …
Approximate Bayesian Computation In Forensic Science, Jessie H. Hendricks
Approximate Bayesian Computation In Forensic Science, Jessie H. Hendricks
The Journal of Undergraduate Research
Forensic evidence is often an important factor in criminal investigations. Analyzing evidence in an objective way involves the use of statistics. However, many evidence types (i.e., glass fragments, fingerprints, shoe impressions) are very complex. This makes the use of statistical methods, such as model selection in Bayesian inference, extremely difficult.
Approximate Bayesian Computation is an algorithmic method in Bayesian analysis that can be used for model selection. It is especially useful because it can be used to assign a Bayes Factor without the need to directly evaluate the exact likelihood function - a difficult task for complex data. Several criticisms …
Bayesian Exponential Random Graph Modelling Of Interhospital Patient Referral Networks, Alberto Caimo, Francesca Pallotti, Alessandro Lomi
Bayesian Exponential Random Graph Modelling Of Interhospital Patient Referral Networks, Alberto Caimo, Francesca Pallotti, Alessandro Lomi
Articles
Using original data that we have collected on referral relations between 110 hospitals serving a large regional community, we show how recently derived Bayesian exponential random graph models may be adopted to illuminate core empirical issues in research on relational coordination among healthcare organisations. We show how a rigorous Bayesian computation approach supports a fully probabilistic analytical framework that alleviates well-known problems in the estimation of model parameters of exponential random graph models. We also show how the main structural features of interhospital patient referral networks that prior studies have described can be reproduced with accuracy by specifying the system …
Teaching Size And Power Properties Of Hypothesis Tests Through Simulations, Suleyman Taspinar, Osman Dogan
Teaching Size And Power Properties Of Hypothesis Tests Through Simulations, Suleyman Taspinar, Osman Dogan
Publications and Research
In this study, we review the graphical methods suggested in Davidson and MacKinnon (Davidson, Russell, and James G. MacKinnon. 1998. “Graphical Methods for Investigating the Size and Power of Hypothesis Tests.” The Manchester School 66 (1): 1–26.) that can be used to investigate size and power properties of hypothesis tests for undergraduate and graduate econometrics courses. These methods can be used to assess finite sample properties of various hypothesis tests through simulation studies. In addition, these methods can be effectively used in classrooms to reinforce students’ understanding of basic hypothesis testing concepts such as Type I error, Type II error, …