Heng Wang

Previous research that has evaluated the effectiveness of personality variables for predicting work performance has predominantly relied on methods designed to detect simple relationships. The research reported in this thesis employed artificial neural networks ??? a method that is capable of capturing complex nonlinear and configural relationships among variables ??? and the findings were compared to those obtained by the more traditional method of linear regression. Six datasets that comprise a range of occupations, personality inventories, and work performance measures were used as the basis of the analyses. A series of studies were conducted to compare the predictive performance of prediction equations that a) were developed using either artificial neural networks or linear regression, and b) differed with respect to the type and number of personality variables that were used as predictors of work performance. Studies 1 and 2 compared the two methods using individual personality variables that assess the broad constructs of the five-factor model of personality. Studies 3 and 4 used combinations of these broad variables as the predictors. Study 5 employed narrow personality variables that assess specific facets of the broad constructs. Additional methodological contributions include the use of a resampling procedure, the use of multiple measures of predictive performance, and the comparison of two procedures for developing neural networks. Across the studies, it was generally found that the neural networks were rarely able to outperform the simpler linear regression equations, and this was attributed to the lack of reliable nonlinearity and configurality in personality-work performance relationships. However, the neural networks were able to outperform linear regression in the few instances where there was some independent evidence of nonlinear or configural relationships. Consequently, although the findings do not support the usefulness of neural networks for specifically improving the effectiveness of personality variables as predictors of work performance, in a broader sense they provide some grounds for optimism for organisational researchers interested in applying this method to investigate and exploit complex relationships among variables.

This thesis considers location and scale parameter modelling of the heteroscedastic t-distribution. This new distribution is an extension of the heteroscedastic Gaussian and provides robust analysis in the presence of outliers as well accommodates possible heteroscedasticity by flexibly modelling the scale parameter using covariates existing in the data. To motivate components of work in this thesis the Gaussian linear mixed model is reviewed. The mixed model equations are derived for the location fixed and random effects and this model is then used to introduce Restricted Maximum Likelihood ( REML ). From this an algorithmic scheme to estimate the scale parameters is developed. A review of location and scale parameter modelling of the heteroscedastic Gaussian distribution is presented. In this thesis, the scale parameters are a restricted to be a function of covariates existing in the data. Maximum Likelihood ( ML ) and REML estimation of the location and scale parameters is derived as well as an efficient computational algorithm and software are presented. The Gaussian model is then extended by considering the heteroscedastic t distribution. Initially, the heteroscedastic t is restricted to known degrees of freedom. Scoring equations for the location and scale parameters are derived and their intimate connection to the prediction of the random scale effects is discussed. Tools for detecting and testing heteroscedasticity are also derived and a computational algorithm is presented. A mini software package " hett " using this algorithm is also discussed. To derive a REML equivalent for the heteroscedastic t asymptotic likelihood theory is discussed. In this thesis an integral approximation, the Laplace approximation, is presented and two examples, with the inclusion of ML for the heteroscedastic t, are discussed. A new approximate integral technique called Partial Laplace is also discussed and is exemplified with linear mixed models. Approximate marginal likelihood techniques using Modified Profile Likelihood ( MPL ), Conditional Profile Likelihood ( CPL ) and Stably Adjusted Profile Likelihood ( SAPL ) are also presented and offer an alternative to the approximate integration techniques. The asymptotic techniques are then applied to the heteroscedastic t when the degrees of freedom is known to form two distinct REMLs for the scale parameters. The first approximation uses the Partial Laplace approximation to form a REML for the scale parameters, whereas, the second uses the approximate marginal likelihood technique MPL. For each, the estimation of the location and scale parameters is discussed and computational algorithms are presented. For comparison, the heteroscedastic t for known degrees of freedom using ML and the two new REML equivalents are illustrated with an example and a comparative simulation study. The model is then extended to incorporate the estimation of the degrees of freedom parameter. The estimating equations for the location and scale parameters under ML are preserved and the estimation of the degrees of freedom parameter is integrated into the algorithm. The approximate REML techniques are also extended. For the Partial Laplace approximation the estimation of the degrees of freedom parameter is simultaneously estimated with the scale parameters and therefore the algorithm differs only slightly. The second approximation uses SAPL to estimate the parameters and produces approximate marginal likelihoods for the location, scale and degrees of freedom parameters. Computational algorithms for each of the techniques are also presented. Several extensive examples, as well as a comparative simulation study, are used to illustrate ML and the two REML equivalents for the heteroscedastic t with unknown degrees of freedom. The thesis is concluded with a discussion of the new techniques derived for the heteroscedastic t distribution along with their advantages and disadvantages. Topics of further research are also discussed. / Thesis (Ph.D.)--School of Agriculture and Wine, 2005.

<p>De svenska bankernas osäkra exponering mot Baltikum har varit en stor debatt i svensk media under en lång period. Den här uppsatsen syftar till att undersöka sambandet mellan de tre baltiska ekonomiernas aktiemarknader och de fyra svenska storbankerna. Vi har valt att lägga stor fokus på storbankernas kreditriskexponering, eftersom den har haft stor fokus på sig i media. För att förbättra trovärdigheten för uppsatsen har vi valt att undersöka ett generalindex för hela Baltikum och jämföra det med den svenska aktiemarknaden. Vi gör det i syfte att kontrollera att sambandet mellan de två marknaderna inte är för stark, eftersom de övriga sambanden vi hittar mellan storbankerna och de baltiska indexen då kan vara ett resultat av en större samvariation. </p><p>Uppsatsen är baserad på en kvantitativ studie, vars datamaterial består av slutkurser från aktieindexen och från storbankernas aktiekurser på daglig basis under tidsperioden 2000-2009. Genom att i vår kvantitativa undersökning utföra en regressions- och korrelationsanalys, vill vi klargöra sambandet mellan de baltiska indexen och de svenska storbankerna. </p><p>Korrelationsanalysen resulterade i ett tydligt starkt samband, orsaken till sambandet kan vi dock inte säkerställa då det kan vara ett resultat av en korrelation mellan den svenska aktiemarknaden och de baltiska aktiemarknaderna. Dessutom förekommer autokorrelation i materialet vilket gör att inga slutsatser kan säkerställas. </p><p>Vidare fann vi ett samband mellan den svenska aktiemarknaden och det baltiska generalindexet i regressionsanalysen. Vilket kan ge ytterligare indikationer för att eventuella trender mellan de fyra storbankerna och de baltiska indexen kan vara ett resultat av sambandet mellan deras tillhörande index. Regressionsanalysen för de fyra storbankerna och de tre baltiska indexen visar på positiva tendenser, dock inte genomgående. </p><p>Även om vi är medvetna om att det inte statistisk går att säkerställa, menar vi, att det samband som dock syns i vår undersökning kan bero på den enorma kreditriskexponering de svenska storbankerna har mot de baltiska ekonomierna. Utifrån de teorier vi har redovisat finns det forskning som visar på att kreditexponering i ett land påverkar ett lands BNP, vidare har vi teori som visar att det finns ett samband mellan BNP och aktieavkastning i ett land. Utifrån den informationen finns det teori utgå från då vi vill undersöka sambandet mellan indexen och aktierna med reala ekonomiska variabler i grunden.</p>

<p>I present an application to visualization of GPS data and Linear Correlations and models. A collection of data for each vehicle is used to compute correlations. Deviating correlations can be indicative of a faulty vehicle.</p><p> The correlation values for each vehicle are computed with use linear regression algorithms using up to 4 signals in the data (with varied time window), and display the model parameters in a window next to the GPS map. Multiple measurements (multiple drive routes and multiple model parameters) are displayed at the same time, allowing tracking over time and comparison of different vehicles.</p><p> </p><p> The whole technique is demonstrated on three data which is set on first frame by user. The results are displayed with a java application and Google Map.</p>

Many rating systems exist that order the Division I teams in Men's College Basketball that compete in the NCAA Tournament, such as seeding teams on an S-curve, and the Pomeroy and Sagarin ratings, simplifying the process of choosing winners to a comparison of two numbers. Rather than creating a rating system, we analyze each matchup by using the difference between the teams' individual regular season statistics as the independent variables. We use an MCMC approach and logistic regression along with several model selection techniques to arrive at models for predicting the winner of each game. When given the 63 actual games in the 2012 tournament, eight of our models performed as well as Pomeroy's rating system and four did as well as Sagarin's rating system when given the 63 actual games. Not allowing the models to fix their mistakes resulted in only one model outperforming both Pomeroy and Sagarin's systems. / McAnulty College and Graduate School of Liberal Arts / Computational Mathematics / MS / Thesis

This thesis advocates the use of maximum likelihood analysis for generalized regression models with measurement error in a single explanatory variable. This will be done first by presenting a computational algorithm and the numerical details for carrying out this algorithm on a wide variety of models. The computational methods will be based on the EM algorithm in conjunction with the use of Gauss-Hermite quadrature to approximate integrals in the E-step. Second, this thesis will demonstrate the relative superiority of likelihood-ratio tests and confidence intervals over those based on asymptotic normality of estimates and standard errors, and that likelihood methods may be more robust in these situations than previously thought. The ability to carry out likelihood analysis under a wide range of distributional assumptions, along with the advantages of likelihood ratio inference and the encouraging robustness results make likelihood analysis a practical option worth considering in regression problems with explanatory variable measurement error. / Graduation date: 1999

IPV is the most common cause of violence-related injury to women in the United States and greater than one-third of all female homicide victims in the U.S. were killed by the victims' husband or partner. Nationally, intimate partner violence (IPV) has been identified as a public health issue, and internationally gender inequality is the number one human rights issue. In addition to risk factors identified among multicultural samples, characteristics that increase Latina vulnerability to IPV may relate to the specific cultural scripts between partners that are expected and supported within Latino culture. Latinas in the United States are affected by a confluence of risk factors for IPV including power imbalances associated with traditional gender roles (machismo, the stereotypical male role, and marianismo, the traditional female role), acculturation, socioeconomic status and education level. Vulnerability to coercive control behaviors resulting in IPV from a partner may be increased if the woman has a previous history of child sexual abuse (CSA). A secondary analysis of selected data from a three year parent study, SEPA II (Salud, Educacion, Prevencion y Autocuidado; Health, Education, Prevention and Self-Care), was undertaken to explore the relationships between CSA, machismo, marianismo, acculturation, socioeconomic status and education on the severity and occurrence of IPV among 548 adult Latinas between the ages of 18 and 50. Selected data elements were analyzed from the Short Form of the Revised Conflict Tactics Scale (CTS2S), the Violence Assessment Questionnaire (VAQ), the M-Measure (machismo), the Attitudes toward Women Scale (marianismo), the Bidimensional Acculturation Scale for Hispanics (BAS) and baseline demographic measures collected on the El Centro Intake Form. Correlations were done to examine the relationships among IPV, CSA, machismo, marianismo, acculturation, SES and education. Logistic regression was used to determine if women who report IPV are more likely to also report a history of CSA, more traditional gender role beliefs, higher levels of acculturation, lower SES and higher education. CTS2S (severity of violence) was significantly correlated with CSA, and the non-Hispanic domain of the BAS. The VAQ measure of violence (occurrence of physical violence > 18 years) also was significantly correlated with CSA, negatively correlated with the Hispanic domain, positively correlated with the Non-Hispanic domain of the BAS, and negatively correlated with monthly income. CSA was negatively associated with the Hispanic domain, positively correlated with the non-Hispanic domain and negatively correlated with years of education. Traditional gender roles did not influence the occurrence or severity of violence in this study. CSA was a significant predictor of IPV among Latinas. Hispanic domain (acculturation) and higher monthly income were protective against IPV among Latinas. Childhood sexual abuse, identification with non-Hispanic culture and decreased SES were found to increase vulnerability to IPV among Latinas. There is a need to design and test interventions and support systems for women that are contextually structured to acknowledge the family and community values as well as the individual needs of Latinas. Interpreting responses to violence for Latinas within the larger context of equality for women becomes part of an international focus aimed at ending gender based violence.

Sample size calculation methods for ordinal logistic regression are proposed to test statistical hypotheses. The author was motivated to do this work by the need for statistical analysis of the red imported fire ants data. The proposed methods use the concept of approximation by the moment-generating function. Some correction methods are also suggested. When a prior data set is available, an empirical method is explored. Application of the proposed methodology to the fire ant mating flight data is demonstrated. The proposed sample size and power calculation methods are applied in the hypothesis testing problems. Simulation studies are also conducted to illustrate their performance and to compare them with existing methods.

De svenska bankernas osäkra exponering mot Baltikum har varit en stor debatt i svensk media under en lång period. Den här uppsatsen syftar till att undersöka sambandet mellan de tre baltiska ekonomiernas aktiemarknader och de fyra svenska storbankerna. Vi har valt att lägga stor fokus på storbankernas kreditriskexponering, eftersom den har haft stor fokus på sig i media. För att förbättra trovärdigheten för uppsatsen har vi valt att undersöka ett generalindex för hela Baltikum och jämföra det med den svenska aktiemarknaden. Vi gör det i syfte att kontrollera att sambandet mellan de två marknaderna inte är för stark, eftersom de övriga sambanden vi hittar mellan storbankerna och de baltiska indexen då kan vara ett resultat av en större samvariation. Uppsatsen är baserad på en kvantitativ studie, vars datamaterial består av slutkurser från aktieindexen och från storbankernas aktiekurser på daglig basis under tidsperioden 2000-2009. Genom att i vår kvantitativa undersökning utföra en regressions- och korrelationsanalys, vill vi klargöra sambandet mellan de baltiska indexen och de svenska storbankerna. Korrelationsanalysen resulterade i ett tydligt starkt samband, orsaken till sambandet kan vi dock inte säkerställa då det kan vara ett resultat av en korrelation mellan den svenska aktiemarknaden och de baltiska aktiemarknaderna. Dessutom förekommer autokorrelation i materialet vilket gör att inga slutsatser kan säkerställas. Vidare fann vi ett samband mellan den svenska aktiemarknaden och det baltiska generalindexet i regressionsanalysen. Vilket kan ge ytterligare indikationer för att eventuella trender mellan de fyra storbankerna och de baltiska indexen kan vara ett resultat av sambandet mellan deras tillhörande index. Regressionsanalysen för de fyra storbankerna och de tre baltiska indexen visar på positiva tendenser, dock inte genomgående. Även om vi är medvetna om att det inte statistisk går att säkerställa, menar vi, att det samband som dock syns i vår undersökning kan bero på den enorma kreditriskexponering de svenska storbankerna har mot de baltiska ekonomierna. Utifrån de teorier vi har redovisat finns det forskning som visar på att kreditexponering i ett land påverkar ett lands BNP, vidare har vi teori som visar att det finns ett samband mellan BNP och aktieavkastning i ett land. Utifrån den informationen finns det teori utgå från då vi vill undersöka sambandet mellan indexen och aktierna med reala ekonomiska variabler i grunden.