Bayesian factor analysis - abstract Factor analysis is a method which enables high-dimensional random vector of measurements to be approximated by linear combinations of much lower number of hidden factors. Classical estimation procedure of this model lies on the cho- ice of the number of factors, the decomposition of variance matrix while keeping identification conditions satisfied and on the appropriate choice of rotation for better interpretation of the model. This model will be transferred into bayesian framework which offers the usage of prior information unlike the classical appro- ach. The number of hidden factors can be considered as a random parameter and the dependency of each measurement on at most one factor can be forced by suitable specification of prior distribution. Estimates of model parameters are based on posterior distribution which is approximated by Monte Carlo Markov Chain methods. Bayesian approach solves the problem of selection of the num- ber of factors, the model estimation and the ensuring of the identifiability and the interpretability at the same time. The ability to estimate the real number of hidden factors is tested in a simulation study. 1

Esse projeto visou a construção, validação e normatização de escalas para a avaliação dos Fatores Extroversão e Socialização no modelo dos Cinco Grandes Fatores de Personalidade. A partir deste Modelo, Socialização é uma dimensão da personalidade que agrupa traços como altruísmo, franqueza, confiança nas pessoas, bem como frieza, falta de empatia, comportamentos antisociais, etc. Extroversão engloba traços que descrevem nível de comunicação, assertividade, gregariedade, busca por diversão, etc. A validade de construto da Escala Fatorial de Socialização (EFS) e Escala Fatorial de Extroversão (EFE) foi realizada a partir de amostras independentes compostas por aproximadamente 1.100 pessoas de cinco estados brasileiros, de ambos os sexos, com nível de escolarização médio ou superior. Foram realizadas análises fatoriais para a verificação da dimensionalidade da EFS, sendo que a solução de três fatores foi considerada a mais adequada. Os fatores extraídos foram denominados Amabilidade, Pró-sociabilidade e Confiança nas pessoas, com Alpha’s de 0,91; 0,84 e 0,80 respectivamente. A escala geral apresentou uma consistência interna de 0,92. Foram realizadas análises fatoriais para a verificação da dimensionalidade da EFE, sendo que a solução de quatro fatores foi considerada a mais adequada. Os fatores extraídos foram denominados Comunicação, Altivez, Assertividade, Interação Social, com Alpha’s de 0,90; 0,78; 0,78 e 0,83 respectivamente. A escala geral apresentou uma consistência interna de 0,91. / The present project aimed the development, validation and standardization of scales to measure Extraversion and Agreeableness in the Five Factor Model of Personality. In this model, Agreeableness is comprised by traits that describe altruism, straightforwardness, trust in people, as well as coldness, antisocial behavior, among others. Extraversion includes traits that describe level of communication, assertivity, gregariousness, search for pleasure, among others. The participants in the construct validity study of the Agreeableness Factorial Scale (EFS) and Extraversion Factorial Scale (EFE) were approximately 1.100 individuals, from five States in Brazil, of both sexes, with high school or university level of education. Factor analyses were conducted to determine the EFS dimensions. A 3-factor solution was found to be more adequate. The factors found were named: Amiableness, Pro-social behavior, and Trust. Cronbach’s alphas were .91, .84, and .80 respectively. The general scale presented an internal consistency level of .92. Factor analyses were also conducted to verify the EFE dimensions. A 4-factor solution was found to be more adequate. The factors found were named: Communication, Pride, Assertiveness, and Social Interaction. Cronbach’s alphas were .90, .78, .78, and .83 respectively. The general scale presented internal consistency level of .91.

Atualmente há uma quantidade considerável de informação sobre o comportamento da economia à disposição da autoridade monetária, cuja decisão é provavelmente baseada nesse grande conjunto de dados. Entretanto, grande parte das análises empíricas de política monetária é baseada em modelos de pequena escala, e o problema de variáveis omitidas pode ser relevante. Uma literatura mais recente mostrou que grandes conjuntos de séries macroeconômicas podem ser modelados usando fatores dinâmicos, que são considerados um resumo da informação contida nos dados. Neste trabalho combinamos os fatores extraídos de 178 séries de tempo com os modelos tradicionais de pequena escala para analisar a política monetária no Brasil. Os fatores estimados são usados como instrumentos em regras de Taylor forward looking e como regressores adicionais em VAR´s. A informação extraída de grandes conjuntos de dados mostrou-se bem útil na análise empírica da política monetária. / Nowadays there is a considerable amount of information on the behavior of the economy available and central bankers can be expected to base their decisions on this very large information set. Nevertheless, most of the empirical analysis of monetary policy has been based on small scale models, and omitted information can be a relevant problem. Recent time-series techniques have shown that large datasets can be modeled using dynamic factors, which are considered a summary of the information in the data. In this work we combine the factors extracted from 178 time series with more traditional small scale models to analyze monetary policy in Brazil. The estimated factors are used as instruments in forward looking Taylor rules and as additional regressors in VAR´s. The information extracted from large datasets turns out to be quite useful for the empirical analysis of monetary policy.

Because of their seemingly universal appeal, game elements such as points, goals and leaderboards, are increasingly being incorporated into non-entertainment situations with the aim of increasing user performance. This process is referred to as gamification. However, little empirical research exists on gamification’s effectiveness in enhancing performance, particularly with respect to moderating influence of user personality traits. Social gamification that involves more than one participant incorporates social interdependence, which takes form as negative interdependence (competitive in nature) or positive interdependence (cooperative in nature). Based on the hypothesis that the interdependence type underlying a gamification system would appeal to differing personality traits, this study reports a quasi-experiment involving a platform designed to manipulate participant interdependence structure among cooperation, competition, and neutrality, with the latter acting as the control condition. These three interdependence structures functioned as the experiment’s independent variable, with measures of participant performance as dependent variables, together with the participant personality traits assessed using the five factor model of personality acting as moderating variables. 294 undergraduate participants worked with the platform on a voluntary basis over an eight-week period, spending 38,180 minutes and performing 3,275 actions. At the conclusion of the experiment, the data collected were analysed using Kruskal-Wallis, ANOVAs, multilevel mixed method regression models, and a generalised estimating equation. The study’s results yield significant evidence that incorporating gamification in the experimental platform increases participant performance as measured by completed actions on the platform, and that participant personality traits moderated performance depending on interdependence structure. Significant results suggest that within the gamified platform, Extraversion positively moderates performance under competition and Openness positively moderates performance under cooperation.

Human behavior varies widely as does the design of spoken dialog systems (SDS). The search for predictors to match a user’s preference and efficiency for a specific dialog interface type in an SDS was the focus of this research. By using personality as described by the Five-Factor Method (FFM) and the Wizard of Oz technique for delivering three system initiatives of the SDS, participants interacted with each of the SDS initiatives in scheduling an airline flight. The three system initiatives were constructed as strict system, which did not allow the user control of the interaction; mixed system, which allowed the user some control of the interaction but with a system override; and user system, which allowed the user control of the interaction. In order to eliminate gender bias in using the FFM as the instrument, participants were matched in gender and age. Participants were 18 years old to 70 years old, passed a hearing test, had no disability that prohibited the use of the SDS, and were native English speakers. Participants completed an adult consent form, a 50-question personality assessment as described by the FFM, and the interaction with the SDS. Participants also completed a system preference indication form at the end of the interaction. Observations for efficiency were recorded on paper by the researcher. Although the findings did not show a definitive predictor for a SDS due to the small population sample, by using a multinomial regression approach to the statistical analysis, odds ratios of the data helped draw conclusions that support certain personality factors as important roles in a user’s preference and efficiency in choosing and using a SDS. This gives an area for future research. Also, the presumption that preference and efficiency always match was not supported by the results from two of the three systems. An additional area for future research was discovered in the gender data. Although not an initial part of the research, the data shows promise in predicting preference and efficiency for certain SDS. Future research is indicated.

This study is a comparative analysis of the personality characteristics of a sample of World of Warcraft players (n = 147) and a large normative sample (n = 20,993). The 120-item International Personality Item Pool, based on the five factor model, is used. Independent t-tests were conducted and statistical significance was found for some factors; however, the effect sizes were small, indicating a limited practical difference between the two groups.

The significance of credit risk models has increased with the introduction of new Basel accord known as Basel II. The aim of this study is default rate modeling. This thesis follows the two possible approaches of a macro credit risk modeling. First, empirical models are investigated. Second, a latent factor model based on Merton's idea is introduced. Both of these models are derived from individual default probability models. We employed data over the time period from 1988 to 2003 of the Finnish economy in the first part of this thesis. Time series of bankruptcy and firm's numbers were used. Aggregate data for whole economy as well as industry specific data were available. First, linear vector autoregressive models was used in case of dynamic empirical model. We examined how significant macroeconomic indicators determined the default rate in the whole economy and in the industry specific sector. However these models cannot provide microeconomic foundation as latent factor models. We employed a one- factor model in our estimation although, multi-factor models were also considered. A one-factor model was estimated using disaggregated industrial data. This estimation can help understand relation between credit risk and macroeconomic indicators. Obtained results were used in the second part of this...

Chronic or prolonged stress has been shown to have deleterious impacts on mental health, physical health, and cognitive functioning. However, not all individuals show the negative effects of continued exposure to stress. Past research has identified personality as a contributor to resiliency, while also identifying it as an important predictor of negative outcomes, such as psychopathology. More recently, personality researchers have emphasized the importance of examining personality at the level of specific underlying facets, as it can provide a more refined and predictive picture than higher-order personality traits. The current study examined the predictive utility of personality facets in regard to risk and resiliency in high-achieving individuals exposed to transient and chronic stress. Results indicated personality facets provided strong prediction of mental health and behavioral functioning outcomes, and added to the understanding of the association among personality and functioning. In particular, hierarchical linear modeling analyses identified significant risk and protective facets prior to the inclusion of stress and also when interacting with stress. The implications of these analyses, such as identification of particular strategies for boosting protective facets and limiting harmful facets, is discussed.

The content of this master’s thesis is proposal of business plan for setting up company 123fotky s.r.o., which will run microphotobank. This name is used for photobank which sells photographs with non-exclusive rights in other words with royalty free license. Features specific for successful business plan are included in theoretical part. Analytical part provides view on environment in which will the new company operate. The main proposal of business plan is based on theoretical knowledge of this environment and on market analysis.

Syftet med studien var att undersöka om det fanns några samband mellan femfaktormodellen och copingstrategier hos universitetsstudenter i Sverige, samt vilka personlighetsegenskaper som relaterade till de olika copingstrategierna. Genom att använda kvantitativ metod konstruerades ett enkätformulär som publicerades i olika grupper på Facebook. Studien gick ut på att undersöka hur de fem personlighetsdimensionerna utåtriktning, vänlighet, målmedvetenhet, känslomässig instabilitet och öppenhet relaterade till fyra utvalda copingstrategier: aktiv coping, undvikande coping, beteendemässig frånkoppling och nyttjande av emotionellt stöd. Vi använde oss av olika teorier kring vad som påverkar individers val av copingstrategier. Teorierna säger emot varandra och därför ville vi betrakta vår studie som ytterligare ett bidrag till forskningen, för att analysera vilken teori vår undersökning stöttar. Totalt deltog 121 personer i studien och datan analyserades genom multipla linjära regressionsanalyser, detta för att belysa vilka personlighetsegenskaper som predicerade vilka copingstrategier. Våra hypoteser var att utåtriktning skulle vara associerat med hög aktiv coping, att känslomässig instabilitet skulle vara associerat med högt nyttjande av emotionellt stöd och låg aktiv coping och att målmedvetenhet skulle vara associerat med hög aktiv coping. Genom multipla linjära regressionsanalyser visade resultaten i studien på att personlighetsegenskaperna utåtriktning, målmedvetenhet och känslomässig instabilitet predicerade aktiv coping positivt. Personlighetsegenskaperna utåtriktning och målmedvetenhet predicerade undvikande coping negativt. Personlighetsegenskaperna utåtriktning och målmedvetenhet predicerade beteendemässig frånkoppling negativt. Personlighetsegenskaperna utåtriktning och vänlighet predicerade emotionell coping positivt.Vi drog slutsatsen att det fanns en stark koppling mellan de fem personlighetsegenskaperna och de fyra copingstrategierna. / The purpose of this study was to examine whether there were any associations between the big five and coping strategies among university students in Sweden, as well as to examine which personality traits that would predict the different coping strategies. By using quantitative method, a survey was constructed and published in various groups on Facebook. The aim of the study was to examine if the five personality dimensions: extraversion, agreeableness, conscientiousness, neuroticism and openness would relate to four selected coping strategies: active coping, denial coping, behavioral disengagement and use of emotional support. We used theories on what influences individuals' choices of coping strategies. The theories contradict each other and therefore we wanted to consider our study as another contribution to the research area, to analyze which theory our study supports. A total of 121 people participated in the study and we analyzed the data through multiple linear regression analyzes, in order to shed a light on which personality traits predicted which coping strategies. Our hypotheses were that extraversion would be associated with high active coping, that neuroticism would be associated with high use of emotional support and low active coping, and that conscientiousness would be associated with high active coping. Through multiple linear regression analyzes, the results of the study showed that the personality traits extraversion, conscientiousness and neuroticism predicted active coping positively. The personality traits extraversion and conscientiousness predicted the denial coping strategy negatively. The personality traits extraversion and conscientiousness predicted behavioral disengagement negatively. The personality traits extraversion and agreeableness predicted use of emotional support positively. We concluded that there was a strong association between the big five personality traits and the four coping strategies.