Statistical Models Commons^™

A Monte Carlo Analysis Of Seven Dichotomous Variable Confidence Interval Equations, Morgan Juanita Dubose

Masters Theses & Specialist Projects

Department of Psychological Sciences Western Kentucky University There are two options to estimate a range of likely values for the population mean of a continuous variable: one for when the population standard deviation is known and another for when the population standard deviation is unknown. There are seven proposed equations to calculate the confidence interval for the population mean of a dichotomous variable: normal approximation interval, Wilson interval, Jeffreys interval, Clopper-Pearson, Agresti-Coull, arcsine transformation, and logit transformation. In this study, I compared the percent effectiveness of each equation using a Monte Carlo analysis and the interval range over a range …

Death-Related Anxiety Associated With Riskier Decision-Making Irrespective Of Framing: A Bayesian Model Comparison, Blaine Tomkins

Psychology Faculty Publications

A commonly reported finding is that anxious individuals are less likely to make risky decisions. However, no studies have examined whether this association extends to death-related anxiety. The present study examined how groups low, moderate, and high in death-related anxiety make decisions with varying levels of risk. Participants completed a series of hypothetical bets in which the probability of a win was systematically manipulated. High-anxiety individuals displayed the greatest risk-taking behavior, followed by the moderate-anxiety group, with the low-anxiety group being most risk-averse. Experiment 2 tested this association further by framing outcomes in terms of losses, rather than gains. A …

Exploring The Relationship Between Mandatory Helmet Use Regulations And Adult Cyclists’ Behavior In California Using Hybrid Machine Learning Models, Fatemeh Davoudi Kakhki, Maria Chierichetti

Mineta Transportation Institute

In California, bike fatalities increased by 8.1% from 2015 to 2016. Even though the benefits of wearing helmets in protecting cyclists against trauma in cycling crash has been determined, the use of helmets is still limited, and there is opposition against mandatory helmet use, particularly for adults. Therefore, exploring perceptions of adult cyclists regarding mandatory helmet use is a key element in understanding cyclists’ behavior, and determining the impact of mandatory helmet use on their cycling rate. The goal of this research is to identify sociodemographic characteristics and cycling behaviors that are associated with the use and non-use of bicycle …

Science Is For Everybody: A Resource For Understanding Glaciers, Climate, And Modeling, Emma Watson

Independent Study Project (ISP) Collection

Climate change threatens the existence of glaciers worldwide. In order to properly interact with these changing systems, we must first understand them. Glacial models provide an excellent way to do this; however, the language and mathematical concepts used in their creation is generally inaccessible to a common audience. This project presents an online resource for a general audience to interact with climate science, glaciology, and glacial modeling. Long term goals for the project include the incorporation of a glacial model of Drangajökull, Vestfirðir, NW Iceland. As such, focus for the project includes a literature review of glaciers, Drangajökull in particular, …

Development Of A Statistical Model To Predict Materials’ Unit Prices For Future Maintenance And Rehabilitation In Highway Life Cycle Cost Analysis, Changmo Kim, Ghazan Khan, Brent Nguyen, Emily L. Hoang

Mineta Transportation Institute

The main objectives of this study are to investigate the trends in primary pavement materials’ unit price over time and to develop statistical models and guidelines for using predictive unit prices of pavement materials instead of uniform unit prices in life cycle cost analysis (LCCA) for future maintenance and rehabilitation (M&R) projects. Various socio-economic data were collected for the past 20 years (1997–2018) in California, including oil price, population, government expenditure in transportation, vehicle registration, and other key variables, in order to identify factors affecting pavement materials’ unit price. Additionally, the unit price records of the popular pavement materials were …

Working Children On Java Island 2017, Yuniarti

English Language Institute

Children's wellbeing has currently become a global concern as many of them are engaged in the labor force. A small area estimation (SAE) technique, EBLUP under Fey Herriot model, is employed to reveal their number in regencies of Java Island. Statistics have been disaggregated by geographical location (urban/rural) and gender. These statistics are required by the government as the basis for policy making.

Italian Sociologists: A Community Of Disconnected Groups, Aliakbar Akbaritabar, Vincent Traag, Alberto Caimo, Flaminio Squazzoni

Articles

Examining coauthorship networks is key to study scientific collaboration patterns and structural characteristics of scientific communities. Here, we studied coauthorship networks of sociologists in Italy, using temporal and multi-level quantitative analysis. By looking at publications indexed in Scopus, we detected research communities among Italian sociologists. We found that Italian sociologists are fractured in many disconnected groups. The giant connected component of the Italian sociology could be split into five main groups with a mixture of three main disciplinary topics: sociology of culture and communication (present in two groups), economic sociology (present in three groups) and general sociology (present in three …

Analyzing Competitive Balance In Professional Sport, Kevin Alwell

Honors Scholar Theses

In this paper we review several measures to statistically analyze competitive balance and report which leagues have a wider variance of performance amongst its competitors. Each league seeks to maintain high levels of parity, making matches and overall season more unpredictable and appealing to the general audience. Here we quantify competitive advantage across major sports leagues in numbers using several statistical methods in order for leagues to optimize their revenue.

Interdependence Across Foreign Exchange Rate Markets- A Mixed Copula Approach, Richard Adjei-Boateng

Masters Theses & Specialist Projects

The purpose of this thesis is to study the dependence structure of exchange rate pairs using a mixture of copula as opposed to a single copula approach. Mixed copula models have the ability to generate dependence structures that do not belong to existing copula families. The flexibility in choosing component copulas in this mixture model aids the construction of a system that is simultaneously parsimonious and flexible enough to generate most dependence patterns in exchange rate data. Furthermore, the method of mixture copulas facilitates the separation of both the structure and degree of dependence, concepts that are respectively embodied in …

A Monte Carlo Analysis Of Standard Error-Based Methods For Computing Confidence Intervals, Elayna Wichert

Masters Theses & Specialist Projects

The objective of this study is to empirically test existing techniques to calculate the likely range of values for a Classical Test Theory true score given an observed score. The traditional method for forming these confidence intervals has used the standard error of measurement (SEM) as the basis for this confidence interval. An alternate equation, the standard error of estimate (SEE), has been recommended in place of the SEM for this purpose, yet it remains overlooked in the field of psychometrics. It is important that the correct equation be used in various applications in personnel psychology. Monte Carlo analyses were …

Modelling Interactions Among Offenders: A Latent Space Approach For Interdependent Ego-Networks, Isabella Gollini, Alberto Caimo, Paolo Campana

Articles

Illegal markets are notoriously difficult to study. Police data offer an increasingly exploited source of evidence. However, their secondary nature poses challenges for researchers. A key issue is that researchers often have to deal with two sets of actors: targeted and non-targeted. This work develops a latent space model for interdependent ego-networks purposely created to deal with the targeted nature of police evidence. By treating targeted offenders as egos and their contacts as alters, the model (a) leverages on the full information available and (b) mirrors the specificity of the data collection strategy. The paper then applies this approach to …

Evaluation Of Modern Missing Data Handling Methods For Coefficient Alpha, Katerina Matysova

College of Education and Human Sciences: Dissertations, Theses, and Student Research

When assessing a certain characteristic or trait using a multiple item measure, quality of that measure can be assessed by examining the reliability. To avoid multiple time points, reliability can be represented by internal consistency, which is most commonly calculated using Cronbach’s coefficient alpha. Almost every time human participants are involved in research, there is missing data involved. Missing data means that even though complete data were expected to be collected, some data are missing. Missing data can follow different patterns as well as be the result of different mechanisms. One traditional way to deal with missing data is listwise …

Modelling Weighted Signed Networks, Alberto Caimo, Isabella Gollini

Conference papers

In this paper we introduce a new modelling approach to analyse weighted signed networks by assuming that their generative process consists of two models: the interaction model which describes the overall connectivity structure of the relations in the network without taking into account neither the weight nor the sign of the dyadic relations; and the conditional weighted signed network model describes how the edge signed weights form given the interaction structure. We then show how this modelling approach can facilitate the interpretation of the overall network process. Finally, we adopt a Bayesian inferential approach to illustrate the new methodology by …

Best Probable Subset: A New Method For Reducing Data Dimensionality In Linear Regression, Elieser Nodarse

FIU Electronic Theses and Dissertations

Regression is a statistical technique for modeling the relationship between a dependent variable Y and two or more predictor variables, also known as regressors. In the broad field of regression, there exists a special case in which the relationship between the dependent variable and the regressor(s) is linear. This is known as linear regression.

The purpose of this paper is to create a useful method that effectively selects a subset of regressors when dealing with high dimensional data and/or collinearity in linear regression. As the name depicts it, high dimensional data occurs when the number of predictor variables is far …

Pawnee Dam Inflow Design Flood (Idf) Update And Stage-Frequency Curve Development Using Rmcrfa, Jennifer P. Christensen, Joshua J. Melliger

United States Geological Survey: Water Reports and Publications

Pawnee Dam is one of the ten Salt Creek Dams designed and built in the 1960s to mitigate flooding in Lincoln, Nebraska. This short paper illustrates the update of the Pawnee Dam inflow design flood (IDF) through calibration to recent high flow events and the development of its stage-frequency or hydrologic loading curve with the U.S. Army Corps of Engineers’ Risk Management Center Reservoir Frequency Analysis (RMC-RFA) model. The IDF update follows Engineering Regulation 1110-8-2, Inflow Design Flood for Dams and Reservoirs, including unit hydrograph peaking and two antecedent pool elevations. Background information on the original design of the dam …

International Risk Sharing In Overlapping Generations Models, James Staveley-O'Carroll, Olena M. Staveley-O'Carroll

Economics Department Working Papers

We present a solution to the Backus-Smith puzzle that, instead of relying on extreme parameter values or complex modeling assumptions, simply switches the framework from infinitely lived agents to overlapping generations. Young agents face non-diversifiable wage risk that leads to a low degree of risk sharing within each country. Subsequently, international price movements are not sufficient to achieve the high consumption-real exchange rate correlation produced in standard infinitely lived agent DSGE models.

Nonlinearities In The Real Exchange Rates: New Evidence From Developed And Developing Countries, Yamin S. Ahmad, Ming Chien Lo, Olena M. Staveley-O'Carroll

Economics Department Working Papers

This paper investigates nonlinearities in the dynamics of real exchange rates. We use Monte Carlo simulations to establish the size properties of the Teräsvirta-Anderson (1992) and the Teräsvirta (1994) test, when the dynamics of the real exchange rate is influenced by an exogenous process. In addition, we examine the modification proposed by Ahmad, Lo and Mykhaylova (2013; Journal of International Economics) to show that the modified nonlinearity test performs much better than the original in both Monte Carlo exercises and in the actual data on 1431 bilateral real exchange rate series. Finally, we investigate the dynamics of the real exchange …

Motivational Interviewing Treatment Integrity (Miti), Himal Adhikari

Criminal Justice Data

This report summarizes interview data collected using MITI, by the Stearns County Community Corrections. The 42 interviews of corrections clients were held between 2015 and 2017. They were examined to determine the effectiveness of interviewing techniques using criteria established on the MITI form. Overall effectiveness measures are given, as well as correlations among some of the quantitative measurements.

Working Relationship Between Clients And Agents At Stearns County Community Corrections, Catherine Fontana

Criminal Justice Data

Stearns County Community Corrections surveyed its Clients for a month on the Client-Agent working relationship. The responses were on a 7-point scale with 1 being the lowest and 7 the highest. For ease of analysis, the responses were divided into low (1-3), medium (4-5) and high (6-7). The results were analyzed by question, program, age, gender, race, supervision time, and individual Agent. All results are available in table and graph form in the appendix. Lastly, Stearns County Community Corrections was compared to Ramsey County Community Corrections. Given the data available, a different categorization was used with low (1-3), medium (4), …

Rock Paper Scissors And Evolutionary Game Theory, Christian Cordova, Rudolf Jovero, Evan Thomas

Math 365 Class Projects

In Rock Paper Scissors (RPS), three different "species" compete, but no single species has a dominating strategy. In evolutionary game theory, replicator equations model population densities over time. When a mutation is introduced, they are called "replicator-mutator" equations. Using the replicator-mutator equation in [1] we have shown how population density of three species change.

Burden Of Atopic Dermatitis In The United States: Analysis Of Healthcare Claims Data In The Commercial, Medicare, And Medi-Cal Databases, Sulena Shrestha, Raymond Miao, Li Wang, Jingdong Chao, Huseyin Yuce, Wenhui Wei

Publications and Research

Comparative data on the burden of atopic dermatitis (AD) in adults relative to the general population are limited. We performed a large-scale evaluation of the burden of disease among US adults with AD relative to matched non-AD controls, encompassing comorbidities, healthcare resource utilization (HCRU), and costs, using healthcare claims data. The impact of AD disease severity on these outcomes was also evaluated.

A General Approach For Predicting The Behavior Of The Supreme Court Of The United States, Daniel Katz

All Faculty Scholarship

Building on developments in machine learning and prior work in the science of judicial prediction, we construct a model designed to predict the behavior of the Supreme Court of the United States in a generalized, out-of-sample context. To do so, we develop a time-evolving random forest classifier that leverages unique feature engineering to predict more than 240,000 justice votes and 28,000 cases outcomes over nearly two centuries (1816-2015). Using only data available prior to decision, our model outperforms null (baseline) models at both the justice and case level under both parametric and non-parametric tests. Over nearly two centuries, we achieve …

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 …

The Impacts Of Telecommuting On The Time-Space Distribution Of Daily Activities, Mario Benito Rojas Iv

FIU Electronic Theses and Dissertations

As major cities have aged, they have also met or exceeded their transportation infrastructure’s capacity. This has led to many negative impacts such as increased greenhouse gas emissions, delay, travel time, congestion, as well as decreased energy independence, standard of living for the cities’ inhabitants and the world as a whole. As a result, these cities will undoubtedly suffer and will struggle to meet the needs of their citizens. It is becoming more evident, and relevant, that the solution to today’s and tomorrow’s transportation problems will be overcome through the use of policy as well as innovative strategies, one of …

Stationary Points For Parametric Stochastic Frontier Models, William C. Horrace, Ian A. Wright

Center for Policy Research

The results of Waldman (1982) on the Normal-Half Normal stochastic frontier model are generalized using the theory of the Dirac delta (Dirac, 1930), and distribution-free conditions are established to ensure a stationary point in the likelihood as the variance of the inefficiency distribution goes to zero. Stability of the stationary point and "wrong skew" results are derived or simulated for common parametric assumptions on the model. Identification is discussed.

Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang

COBRA Preprint Series

Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …

Gis-Integrated Mathematical Modeling Of Social Phenomena At Macro- And Micro- Levels—A Multivariate Geographically-Weighted Regression Model For Identifying Locations Vulnerable To Hosting Terrorist Safe-Houses: France As Case Study, Elyktra Eisman

FIU Electronic Theses and Dissertations

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to …

Time Series Analysis For Psychological Research: Examining And Forecasting Change, Andrew T. Jebb, Louis Tay, Wei Wang, Qiming Huang

Publications and Research

Psychological research has increasingly recognized the importance of integrating temporal dynamics into its theories, and innovations in longitudinal designs and analyses have allowed such theories to be formalized and tested. However, psychological researchers may be relatively unequipped to analyze such data, given its many characteristics and the general complexities involved in longitudinal modeling. The current paper introduces time series analysis to psychological research, an analytic domain that has been essential for understanding and predicting the behavior of variables across many diverse fields. First, the characteristics of time series data are discussed. Second, different time series modeling techniques are surveyed that …

Do Footprint-Based Cafe Standards Make Car Models Bigger?, Brianna Marie Jean

Economics

Corporate Average Fuel Economy (CAFE) standards have historically been set equal across all manufacturer fleets of the same type. Concerns about varying costs across firms and safety implications of standards that are set homogeneously across firms and models resulted in a policy shift towards footprint-based standards. Under this type of standard, individual car models face targets based on the size of the area between the wheelbase and wheel track, so that larger models face less stringent standards, and manufacturers who make, on average, larger cars will face a lighter fleet standard. Theoretical models have shown that this type of policy …

Best Practice Recommendations For Data Screening, Justin A. Desimone, Peter D. Harms, Alice J. Desimone

Department of Management: Faculty Publications

Survey respondents differ in their levels of attention and effort when responding to items. There are a number of methods researchers may use to identify respondents who fail to exert sufficient effort in order to increase the rigor of analysis and enhance the trustworthiness of study results. Screening techniques are organized into three general categories, which differ in impact on survey design and potential respondent awareness. Assumptions and considerations regarding appropriate use of screening techniques are discussed along with descriptions of each technique. The utility of each screening technique is a function of survey design and administration. Each technique has …