Tuberculosis (TB) is a two-stage disease, acquisition of infection and progression to disease. A complex interaction exists between the individual and their environment that determines who acquires infection and who progresses to disease. According to TB literature, 10% of individuals with infection will develop TB disease (1;2). Tuberculosis has been described a disease of poverty, but other factors may be important. The contribution of both individual measures, such as ethnic origin, gender and age and area-level measures, or socio-economic factors, to this two-stage process is not well understood. Understanding tuberculosis epidemiology and identifying those at risk for developing TB is important for effectively controlling the disease. The objective of this study was to determine the individual (age, gender, ethnic origin, geographic location) and area-level measures (income, home ownership, housing density, education, and employment) that contribute to the progression from tuberculosis infection to disease. Data from all Canadian-born Caucasians, Status Indians, and non-Status Indians and Metis, with an initial positive tuberculin skin test (TST) documented in the Saskatchewan TB Control database from January 1, 1986 to January 31, 2002 was analyzed. Exclusion criteria included any previous BCG vaccination, treatment for latent TB infection, or missing data. Individual data was obtained from the TB Control database. Area-level measures were obtained by matching individual postal codes with Canada census data to obtain information from enumeration areas. Outcome was time to TB disease at > 1 month following a documented positive tuberculin skin test. Analysis was completed using Cox regression proportional hazards model. 7588 individuals with a positive tuberculin skin test were included in the study and of these 338 (4.5%) developed TB disease. Thirty-four out of 4140 (0.8%) of Caucasians, 183 out of 2649 (6.9%) of Status Indians and 121 out of 799 (15.1%) non-Status Indians and Metis developed TB. The rate of progression to TB was 5.6/1000 person years for the entire study population. The incidence for Caucasians was 0.9/1000 person years, 7.7/1000 person years for Status Indians and 16.0/1000 person years for non-Status Indians and Metis. In the Cox regression model, including individual and area-level measures, the risk factors association with the progression to TB was age and ethnic origin (< 19 years of age HR 3.7, 95% CI 2.8 - 4.8 compared to > 19 years and ethnic origin HR 5.1, 95% CI 3.0 - 8.6 for Status Indians and HR 7.4, 95% CI 4.1-13.3 for non-Status Indians and Metis both compared to Caucasians). No socio-economic factor was consistently associated with progression to disease. We have found that age and ethnic origin are associated with an increased risk of TB infection progressing to disease. The differences in TB rates between Saskatchewan Caucasians and Status Indians, non-Status Indians and Metis can be explained by Grigg's natural history curve of TB epidemiology within a population (3). The Aboriginal population of Saskatchewan is much earlier in its epidemic resulting in higher disease rates compared to the Caucasian population. Identifying those at risk of developing TB and understanding the determinants of TB epidemiology are important for establishing successful TB control programs.

This essay investigating outbound factors by theoretical planning behaviors approach which generate knowledge information sharing component to knowledge workers of IC Testing/Assembly plant. The external essence and factor is divided into Individual-Level Factors, Team-Level Factors and Organizational-Level Factors: Individual-Level factors including motives (Self-Interest factor and altruistic Factor), job satisfaction; Team-Level Factors should be complied with trust, leaderships; Organizational-Level Factors would be concluded with enterprise culture, management constitutions. Investigated objects would be focused on Walton Advanced Engineering Co.,Ltd., after sampling with the IT engineering, I have concluded with the following issues: 1. Self-Interest factor and job satisfactory factor would be greater influence than the altruistic Factor. 2. Leadership is a critical influencing factor in the knowledge sharing process. 3. Trust is an essential factor for knowledge sharing within a group. 4. Culture and reward system are the most influencing factor for knowledge sharing. 5. It is necessary to tie in administrative strategy to raise the wills to share knowledge. 6. Encouraging group members explode the nuclear tacit knowledge benefits a lot to individuals and overall group improvement and growth. 7. It is quite a challenge to enterprise to build the knowledge sharing mechanism. Hoping the conclusions above would benefit to those knowledge works related managers and knowledge owners to inherit and preserver the main essence of knowledge base for their working groups.

Individual-level models are a class of complex statistical models, often fitted within a Bayesian Markov chain Monte Carlo framework, that have been effectively used to model the spread of infectious diseases. The ability of these models to incorporate individual-level covariate information allows them to be highly flexible, and to account for such characteristics as population heterogeneity. However, these models can be subject to inherent uncertainties often found in infectious disease data. As well, their complex nature can lead to a significant computational expense when fitting these models to epidemic data, particularly for large populations. An individual-level model that incorporates a latent grouping structure into the modeling procedure, based on some heterogeneous population characteristics, is investigated. The dependence of this latent conditional individual-level model on a discrete latent grouping variable alleviates the need for explicit, although possibly unreliable, covariate information. A simulation study is used to assess the posterior predictive ability of this model, in comparison to individual-level models that utilize the full covariate information, or that assume population homogeneity. These models are also applied to data from the 2001 UK foot-and-mouth disease epidemic. When attempting to compare complex models fitted within the Bayesian framework, the identification of appropriate model selection tools would be beneficial. The use of deviance information criterion (DIC) as model comparison tool, particularly for the latent conditional individual-level models, is investigated. A simulation study is used to compare five variants of the DIC, and the ability of each DIC variant to select the true model is determined. Finally, an investigation into methods to reduce the computational burden associated with individual-level models is carried out, based on an individual-level model that also incorporates population heterogeneity through a discrete grouping variable. A simulation study is used to determine the effect of reducing the overall population size by aggregating the data into spatial clusters. Reparameterized individual-level models, accounting for the aggregation effect, are fitted to the aggregated data. The effect of data aggregation on the ability of two reparameterized individual-level models to identify a covariate effect, as well as on the computational expense of the model fitting procedure, is explored.

Infectious disease models can be used to understand mechanisms of the spread of diseases and thus, may effectively guide control policies for potential outbreaks. Deardon et al. (2010) introduced a class of individual-level models (ILMs) which are highly flexible. Parameter estimates for ILMs can be achieved by means of Markov chain Monte Carlo (MCMC) methods within a Bayesian framework. Here, we introduce an extended form of ILM, described by Deardon et al. (2010), and compare this model with the original ILM in the context of a simple spatial system. The two spatial ILMs are fitted to 70 simulated data sets and a real data set on tomato spotted wilt virus (TSWV) in pepper plants (Hughes et al., 1997). We find that the modified ILM is more flexible than the original ILM and may fit some data sets better.

Statistical methods that integrate between-individual (IA) and within-family (FA) genetic association analyses can increase statistical power to identify disease susceptibility genes, however combining IA and FA is valid only when the IA are free of population stratification bias (PSB). Existing methods initially test for PSB by comparing IA and FA results using an arbitrary testing level αPSB, typically 5%. Combined analyses are performed if no significant PSB is detected, otherwise analyses are restricted to FA. As a novel alternative, we propose a weighted (WGT) framework that combines the estimate from the most powerful analysis subject to PSB with the most powerful robust FA estimate, using weights based on the p-value from the PSB test. The WGT approach generalizes existing methods by using a continuous weighting function that depends only on the observed PSB p-value instead of a binary one that also depends on specification of an arbitrary PSB testing level αPSB. Simulations of quantitative trait and case-control data show that in comparison to existing methods, the WGT approach has 5% type I error closer to the nominal level, increased (decreased) accuracy for larger (smaller) PSB levels, and overall increased positive predictive value. The resulting PSB correction is SNP-specific and provides a good compromise between type I error control and power in candidate gene or confirmation studies limited to few loci, when PSB is likely and there are no additional empirical data available to correct PSB. We applied the WGT approach to a case-control study of childhood leukemia and a study of diabetes complications with time-to-event outcomes derived from repeated measurements obtained over 17 years of follow-up. To directly analyze the longitudinal measurements without specification of event thresholds, we developed fully Bayesian latent change-point time (LCPT) models for IA and FA. In analogy with the WGT approach, we also considered an extended LCPT model incorporating PSB evidence in analyses combining IA and FA.

Statistical methods that integrate between-individual (IA) and within-family (FA) genetic association analyses can increase statistical power to identify disease susceptibility genes, however combining IA and FA is valid only when the IA are free of population stratification bias (PSB). Existing methods initially test for PSB by comparing IA and FA results using an arbitrary testing level αPSB, typically 5%. Combined analyses are performed if no significant PSB is detected, otherwise analyses are restricted to FA. As a novel alternative, we propose a weighted (WGT) framework that combines the estimate from the most powerful analysis subject to PSB with the most powerful robust FA estimate, using weights based on the p-value from the PSB test. The WGT approach generalizes existing methods by using a continuous weighting function that depends only on the observed PSB p-value instead of a binary one that also depends on specification of an arbitrary PSB testing level αPSB. Simulations of quantitative trait and case-control data show that in comparison to existing methods, the WGT approach has 5% type I error closer to the nominal level, increased (decreased) accuracy for larger (smaller) PSB levels, and overall increased positive predictive value. The resulting PSB correction is SNP-specific and provides a good compromise between type I error control and power in candidate gene or confirmation studies limited to few loci, when PSB is likely and there are no additional empirical data available to correct PSB. We applied the WGT approach to a case-control study of childhood leukemia and a study of diabetes complications with time-to-event outcomes derived from repeated measurements obtained over 17 years of follow-up. To directly analyze the longitudinal measurements without specification of event thresholds, we developed fully Bayesian latent change-point time (LCPT) models for IA and FA. In analogy with the WGT approach, we also considered an extended LCPT model incorporating PSB evidence in analyses combining IA and FA.

This study emphasizes on the Scandinavian soccer leagues team performance and what shapes it. This has been a widely discussed area where previous researchers have focused on factors such as organizational structure, organizational strategy, team level and individual level. The study takes this field to a new level with a combination of these factors in order to conceptualize team performance on a new level. The purpose with this study is to explain how organizational strategy, structure, team level and individual level factors affect team performance, in the Scandinavian elite soccer leagues. In order to investigate this phenomenon we have used a deductive approach. Further, this study emphasizes a quantitative approach where the data has been collected through a document analysis. In this study the findings indicates that the variables that has been chosen are highly correlated to team performance. However, due to the short time frame this study has fostered, it has been hard to generalize how the variables affect team performance. The limitations are that the study´s findings are only based on a two year span, which makes it hard to generalize the results. However, it is clear that the chosen variables have a significant impact on team performance in Scandinavian soccer leagues. The original value of this thesis is a new conceptualization on team performance within the soccer industry.

The current study investigated how individual level cultural values (horizontal individualism, horizontal collectivism, vertical individualism, vertical collectivism, power distance, masculinity/femininity, uncertainty avoidance, and long/short term orientation) relate to the perceived effectiveness of authentic leadership. To ensure cultural diversity, data was collected from participants via Amazon Mechanical Turk (MTurk).The participant pool included 184 participants from the United States, India, and 10 other countries around the world. Of these, 68 (37%) participants identified themselves as female and 116 (63%) identified themselves as male. In order to provide a sample that is more representative of a working population, all participants were employed for an average of at least 20 hours a week in a workplace outside of the home. Data was collected using an online survey. Participants completed measures for individual level cultural values (Horizontal and Vertical Individualism and Collectivism Scale, and Individual Cultural Value Scale), the perceived effectiveness of authentic leadership (modified Authentic Leadership Questionnaire), and demographics. Participants were compensated $0.65 on average for completing the survey.The perceived effectiveness of authentic leadership was found to have significant positive correlations with horizontal individualism, horizontal collectivism, and long/short term orientation and a negative correlation with power distance and masculinity. In a final hierarchical regression model, age, power distance, long term orientation, and horizontal individualism were found to significantly predict 34% of the variance in perceived effectiveness of authentic leadership. The results help to provide a better understanding of hierarchy perceptions in the workplace. They suggest that individuals who value self-expression, less status differences between leaders and follower, and internal perseverance are more likely to endorse an authentic leadership style as being effective in the workplace. These results imply that congruence between employee and supervisor values may be an important factor in determining whether or not authentic leadership is perceived as being effective in the workplace. Further, managers and organizations may want to consider hiring individuals with cultural values that best fit their own values and leadership style. In the future researchers could investigate individual level cultural values as moderators between leadership and workplace outcomes, such as job satisfaction.

No ambiente organizacional, o fenômeno criatividade é resultado da interação de fato-res. Cultura organizacional, disponibilidade de recursos, expertise, liderança, motivação, estratégia, formação de grupos, são exemplos de fatores que exercem influência sobre a criatividade nas organizações. Este trabalho teve por objetivo identificar e organizar nos níveis de indivíduo, de grupo e organizacional os fatores que exercem influência sobre a criatividade no ambiente das organizações. O presente estudo foi elaborado com caráter exploratório e pretendeu ampliar o entendimento do fenômeno criatividade em empresas brasileiras. Os fatores foram identificados a partir de revisão de literatura e questionados por meio de ferramenta quantitativa a fim de coletar a experiência e opinião de profissi-onais de organizações brasileiras reconhecidas por sua capacidade inovadora. O estudo de campo realizado confirmou a importância de cada um dos fatores o que permitiu a construção de um conjunto coerente de fatores que influenciam a criatividade no ambi-ente das organizações. Demonstrou-se ainda por meio dos resultados obtidos, que, con-forme a organização, podem ocorrer ênfase em alguns fatores e redução da importância de outros. Desta forma, considera-se que a consolidação dos fatores em uma estrutura possibilita a elaboração de ações com objetivo de desenvolver e incrementar o potencial criativo das empresas. / Creativity, within the organization environment, is a result from the interaction of sev-eral factors such as organizational culture, resources availability, expertise, leadership, motivation, strategy and group formation. This work did aim to identify and organize these factors in individual, group and organization levels. It was conducted as an ex-ploratory study intending to boost organizational creativity understanding in Brazilian companies. Factors identified in the literature were checked against Brazilian innovation professionals of well-known organizations through quantitative interviews. The research data did corroborate the factor’s importance making possible to build a structure of the factors that influence creativity in organizational context. The results have also demon-strated that there is alternation of importance of these factors according to the organiza-tion profile. As a result is possible to say that having a factor’s structure enable organi-zations to improve their creative potential.

No ambiente organizacional, o fenômeno criatividade é resultado da interação de fato-res. Cultura organizacional, disponibilidade de recursos, expertise, liderança, motivação, estratégia, formação de grupos, são exemplos de fatores que exercem influência sobre a criatividade nas organizações. Este trabalho teve por objetivo identificar e organizar nos níveis de indivíduo, de grupo e organizacional os fatores que exercem influência sobre a criatividade no ambiente das organizações. O presente estudo foi elaborado com caráter exploratório e pretendeu ampliar o entendimento do fenômeno criatividade em empresas brasileiras. Os fatores foram identificados a partir de revisão de literatura e questionados por meio de ferramenta quantitativa a fim de coletar a experiência e opinião de profissi-onais de organizações brasileiras reconhecidas por sua capacidade inovadora. O estudo de campo realizado confirmou a importância de cada um dos fatores o que permitiu a construção de um conjunto coerente de fatores que influenciam a criatividade no ambi-ente das organizações. Demonstrou-se ainda por meio dos resultados obtidos, que, con-forme a organização, podem ocorrer ênfase em alguns fatores e redução da importância de outros. Desta forma, considera-se que a consolidação dos fatores em uma estrutura possibilita a elaboração de ações com objetivo de desenvolver e incrementar o potencial criativo das empresas. / Creativity, within the organization environment, is a result from the interaction of sev-eral factors such as organizational culture, resources availability, expertise, leadership, motivation, strategy and group formation. This work did aim to identify and organize these factors in individual, group and organization levels. It was conducted as an ex-ploratory study intending to boost organizational creativity understanding in Brazilian companies. Factors identified in the literature were checked against Brazilian innovation professionals of well-known organizations through quantitative interviews. The research data did corroborate the factor’s importance making possible to build a structure of the factors that influence creativity in organizational context. The results have also demon-strated that there is alternation of importance of these factors according to the organiza-tion profile. As a result is possible to say that having a factor’s structure enable organi-zations to improve their creative potential.