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.

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.

The study examined school district expenditures in Texas and their correlations with student achievement. The following research question guided this study: Which resource allocations produce statistically significant correlations between the resource allocation variances among school district and student achievement? An ordinal logistic regression analysis included 1009 school districts in the State of Texas, 18 of 26 possible finance function codes provided per-pupil dollar amounts, and 9 of 11 possible demographic categories were utilized for the study. The study held the school district as the unit of analysis. The statistical model was used to regress the dollar amounts categorized by financial function codes and percent student demographics to determine if a relationship existed with the dependent variable of the Texas Education Agency’s defined accountability rating during the 5-year time period—2004-2008. At the national level, there is a long-standing debate over whether the amount of money allocated to education affects student achievement. The literature review presents two sides of the debate concerning whether financial resources make a difference with regard to student achievement as represented through district-level accountability ratings. The research revealed that specific school district resource allocations by function code are statistically significant with regard to district level accountability measures through the Texas Education Agency (TEA) accountability system. However, the odds ratios temper the impact of the significance. The research also revealed that demographics are statistically significant in the State of Texas accountability system. / text

The aim of this work is to decide the real usage of logistic regression in the market research tasks respecting the needs of final users of research results. The main argument for the final decision is the comparison of its output to the output of an alternative classification method used in practice -- a classification tree method. The topic is divided into three parts. The first part describes the theoretical framework and approaches linked to logistic regression (chapter 2 and 3). The second part analyses the experience with the usage of logistic regression in Czech market research companies (chapter 4) and the topic is closed by applying the method on real data and comparing the output to the classification tree output (chapter 5 and 6).

Background: Investigators are often interested in using population-level health administrative data in inflammatory bowel disease (IBD) patients to study disease outcomes, risk factors and treatment effects to enhance knowledge, shape clinical practice and influence health care policy. A major limitation of using health administrative data for these purposes is the lack of detailed clinical data to adjust for the confounding effects of differential disease severity on observed associations. Methods to account for disease severity using administrative variables would offer a major advance to population-level studies in IBD patients. Thus, in this study we aimed to use a cohort of IBD patients from The Ottawa Hospital (TOH) to validate a model that was originally developed in Manitoba for estimating clinical disease course in IBD patients through healthcare utilization measures. Objectives: The objectives of this thesis are: 1) To identify and characterize a reference cohort of IBD patients in the ambulatory clinics of four gastroenterologists from TOH on clinical disease course in the preceding year (reference cohort), based on a Manitoba definition of clinical disease course; 2) To fit a partial proportional odds (PPO) model for predicting IBD course, derived using Manitoba health administrative data, to the reference cohort of IBD patients using Ontario health administrative data; 3) To derive new PPO models of IBD disease course for the reference cohort using Ontario administrative variables and compare model performance; and 4) To apply the models to the Ontario Crohn’s and Colitis cohort (OCCC) to estimate IBD course in Ontario, and compare the distribution to that of the Manitoba IBD population.Methods: We first identified a reference cohort of IBD patients in Ontario from the outpatient clinics at TOH during fiscal year 2015. Through chart review, we classified these patients into one of four clinical disease categories (remission, mild, moderate, or severe) using the Manitoba definition. We linked these patients to Ontario health administrative datasets. Given slight differences in data structure and coding between Manitoba and Ontario, we were unable to directly test the Manitoba model and instead fit a PPO model to the Ontario cohort using analogous administrative variables to those used in the final Manitoba model (“adapted model”). We subsequently derived new PPO models using unique Ontario administrative variables under three strategies: 1) Stepwise variable selection (“stepwise model”); 2) Forced fitting of all variables (“all-variables model”); and 3) Using a two-step modelling algorithm that considered IBD-related hospitalizations separate from other administrative variables (“two-step model”). We then compared model performance from the four strategies. Finally, we applied the models to the Ontario IBD population from 2004 to 2016 and compared model estimates to those from Manitoba. Results: We identified 963 patients with IBD from TOH outpatient clinics, of which 52.3% (n=504) were males, 64.6% (n=622) had Crohn's Disease, and 89.2% (n=859) resided in an urban setting. Based on the Manitoba definition, 64.9% of patients within our reference cohort were classified as remission, while 11.4%, 14.1%, and 9.6% were classified as mild, moderate, and severe disease course, respectively. The adapted model (c-statistic 0.77, goodness-fit p-value 0.28) performed comparably to the other models: the stepwise model (c-statistic 0.77, goodness-fit p-value 0.50), the all-variables model (c-statistic 0.77, goodness-fit p-value 0.53), and the two-step model (c-statistic 0.78, goodness-fit p-value 0.75). The adapted model also resulted in overall similar estimates with regards to the disease course distribution among the Ontario IBD population. However, on closer inspection, our two-step model, in which individuals who had been hospitalized for an IBD-related indication within the past year were assumed to have severe disease, performed better with respect to accurately classifying individuals with moderate or severe disease, without sacrificing discriminative ability. Based on the two-step model, from 2004 to 2016, 89.2-91.2% of the Ontario IBD population was in remission, 0% had mild disease, 2.4-3.2% had moderate disease, and 5.9-8.4% had severe disease. Distribution of disease course among IBD patients in Ontario differed considerably than that in Manitoba. Conclusion: In the absence of clinical information within health administrative data, we present and compare four different models that can be used to partially account for the confounding effect of disease course among IBD patients in future population-based studies using Ontario health administrative data. Given that our models did not perform as originally expected, especially with regards to accurately identifying individuals with more active disease states, we advise researchers to use these models at their own discretion.

För alpina skidåkare mäter man prestationer i så kallad FIS-ranking. Vi undersöker några metoder för hur man kan analysera data där responsen består av ranger som dessa. Vid situationer då responsdata utgörs av urval av ranger finns ingen självklar analysmetod. Det vi undersöker är skillnaderna vid användandet av olika regressionsanpassningar så som linjär, logistisk och ordinal logistisk regression för att analysera data av denna typ. Vidare används bootstrap för att bilda konfidensintervall. Det visar sig att för våra datamaterial ger metoderna liknande resultat när det gäller att hitta betydelsefulla förklarande variabler. Man kan därmed utgående från denna undersökning, inte se några skäl till varför man ska använda de mer avancerade modellerna. / Alpine skiers measure their performance in FIS ranking. We will investigate some methods on how to analyze data where response data is based on ranks like this. In situations where response data is based on ranks there is no obvious method of analysis. Here, we examine differences in the use of linear, logistic and ordinal logistic regression to analyze data of this type. Bootstrap is used to make confidence intervals. For our data these methods give similar results when it comes to finding important explanatory variables. Based on this survey we cannot see any reason why one should use the more advanced models.

To ensure greater success in its regular projects, Abu-Dhabi Police (ADP) is working on: training their project managers, applying project management software, utilising the services of engineering consultants, etc. However, the performance and outcomes of its projects are still not fully meeting the desired expectations. Therefore, a study to understand some of the undermining factors was carried out. A critical literature review was carried out initially where it was established that project delivery and outcomes are affected in part by the three overarching factors of: project managers’ characteristics, organizational culture and project management culture. On this basis a conceptual framework was developed highlighting how these 3 compound factors affect project performance and outcome; and in particular how ADP’s values relate with the competencies of their project managers. The empirical aspects involved the use of mixed methods where the first part was a quantitative survey of the understanding and achievement of both ADP’s 5 values (part of organizational culture) and 15 competencies (part of project manager’s characteristics), as well as the impact of the former on the later. A questionnaire was administered to 157 people for data collection and 71 fully completed responses were obtained, representing a response rate of 45%. Descriptive statistics were used to evaluate the levels of achievement of ADP’s values and competencies, which were found to be high. The analysis went on to use ordered logistic regression to examine the association between the attainment of ADP’s values and competencies. The findings showed that the 5 values impact on the competencies of ADP’s project managers differently; for example, the value of ‘integrity and honesty’ impacts heavily on the 5 competencies of Integration management, Scope management, Time management, Achieving and action, and Leadership; while the value of ‘effective communication’ impacts heavily on the 3 competencies of Scope management, Cost management, and Achieving and action. An advanced training programme was subsequently developed for ADP to further increase the attainment of values and competencies by their project managers. This programme was developed in focus group discussions that involved some selected project managers who had long working experience and high understanding of ADP project schemes. A further round of focus group discussions was also used to validate this advanced training programme.

It is believed that a large number of people experience remaining symptoms after COVID-19, so-called post-COVID. The formal definition and diagnostic criteria of post-COVID have been a scientific controversy. So far, there is no reliable system for distinguishing the severity of post-COVID. This type of measurement would be helpful in future targeted therapies. Therefore, this thesis aims to evaluate the relationship between an individual’s functional status today and the symptoms present as well as identify relevant groups of post-COVID based on these 17 long-term symptoms of post-COVID. Further, to produce a model for which of these groups an individual belongs to. By using cluster analysis and ordinal logistic regression, Post-COVID Syndrome scores are produced. That is based upon both subjects who were hospitalised and those who were not, collected through a project called COMBAT post-covid. The individuals are then divided into groups based on these scores, and a prediction model is made using ordinal logistic regression and backward deletion. Three well-separated groups of post-COVID are found based on the produced scores. The prediction model indicates that the nine variables Sex, BMI, Smoking, Snuff, Heart disease, Lung disease, Diabetes, Chronic pain and Symptom severity at the onset seem important for predicting someone’s group. This study showed that the remaining symptoms affected an individual’s functional status, including self-reported working ability and general health.

In today’s information era, many news outlets are competing for attention. One way to cut through the noise is to use images. Obtaining images can be both time-consuming and expen- sive for smaller news agencies. In collaboration with the Swedish news agency Newsworthy, we investigate the possibilities of using AI-generated images in a journalistic context. Using images generated with the text-to-image generation model Stable Diffusion, we aim to answer the research question How do the parameters in Stable Diffusion affect the applicability of the generated images for journalistic purposes? A total of 511 images are generated with different Stable Diffusion parameter settings and rated on a scale of 1-5 by three journalists at Newswor- thy. The data is analyzed using ordinal logistic regression. The results suggest that the optimal value for the Stable Diffusion parameter classifier-free guidance is around 10-12, the default 50 iterations are sufficient, and keywords do not significantly affect the image outcome. The parameter that has the single greatest effect on the outcome is the prompt. Thus, to generate photo-realistic images that can be used in a journalistic context, most thought and effort should be put towards formulating a suitable prompt.

This dissertation examines the association between transformational leadership and public organizational performance using different data and methods. Each of the three articles collected in this dissertation contributes to the scholarship exploring the interplay of transformational leadership and organizational performance using distinct data and interpretive methods, examining the interplay of its elements and a widely used outcome measure – organizational performance as a dependent variable. The first article presents evidence of the empirical studies analyzing the association between transformational leadership and public organizational performance. Based on a formal, replicable search method informed by current practices for the systematic evaluation of published evidence, this review collects and analyzes empirical research articles examining the association between transformational leadership and public organizational performance. A total of seven journal articles were identified that met the study criteria. The measures of the transformational leadership construct in these studies are different but show a common pattern of survey questionnaires with multiple-level responses. Moreover, transformational leadership is found to be positively associated with public organizational performance. Organizational performance is operationalized using several factors such as development, growth, creativity, and effectiveness in the included studies. Acknowledging the gap in the included studies, this review offers two research questions for further exploration to address the gaps in the existing studies. The second article explores the association between the elements of transformational leadership and federal organizational performance in very large and large federal agencies using Ordinal Logistic Regression (OLR) on quantitative survey data drawn from results of the OPM Federal Employment Viewpoint Survey. Statistical findings of this study show a positive relationship between the elements of transformational leadership and organizational performance. This study contributes to the transformational leadership and public management literature by adding the scholarship exploring the association between the elements of transformational leadership and public organizational performance. The third article explores the association between transformational leadership and organizational performance from the experiences and perspectives of U.S. federal agency employees. The data was collected through semi-structured interviews with federal leaders from very large and large agencies, as per the Office of Personnel Management's classification. The perceptions of federal employees reflect the interplay between transformational leadership behaviors and perceptions of organizational performance. The informants' interviews enhance the understanding of transformational leadership-organizational performance association from the employee perspective. A process of thematic coding and interpretation is employed to analyze the interview data. The study findings contribute to the management and leadership literature by exploring the lived experiences of federal employees and their perceptions of the influence of transformational leadership on organizational performance. Moreover, the replicable qualitative interview process and analysis methodology create a pathway for future qualitative research. / Doctor of Philosophy / The influence of leadership is widely studied in terms of organizational performance. Among the leadership theories thought to influence organizational performance, transformational leadership is the most widely studied theory. The theory has gained much attention in the past 40 years for its contribution to many positive organizational outcomes, including meaningful work, organizational commitment, job satisfaction, and organizational performance. Despite a rich history of research in positive organizational outcomes, scholars still argue that there are scopes further to advance the empirical research on transformational leadership theory. Hence, the purpose of this dissertation is to address this claim and analyze the interplay between transformational leadership and public organizational performance. Study findings will contribute to the literature on transformational leadership by empirically examining the interplay of its elements and federal organizational performance. Moreover, the application of three distinct methods and interpretative data analysis will add new evidence to the research of public management and leadership.