Approved for public release, distribution is unlimited / This study analyzes the relationship between selection to major in the Marine Corps, and the survival of midgrade officers to the promotion point of major, by investigating the effects of billet assignments. Specifically, this study looks at the influence of the percentage of time spent in the Fleet Marine Forces (FMF), the percentage of time spent in primary military occupation (PMOS) billet assignments, and the effect of having served in combat, recruiting, security forces, joint, and drill field duties. Models were formulated using groundwork established in previous promotion, retention, and attrition studies. Assignment variables were then introduced to the models. To account for officers' choice for continued service vice forced attrition, the sample was restricted to officers who had attained five years of service. Probit regression was used to find the influence of career assignments on the probability of selection; Heckman's correction was used to control for self-selection bias; and, Cox proportionalhazard regression was used, utilizing the same assignment factors, to find the influence of assignments on the likelihood of attrition. The findings indicated that FMF and PMOS ratios above 60 percent had a negative effect on promotion and retention. Also indicated was that time spent outside the PMOS, in "B" billets, had a positive effect on retention. In a time of budgetary constraints, this information may provide assistance to personnel planners as an alternative to pecuniary measures used to maintain and shape the force. / Major, United States Marine Corps

Revisión por pares

Submitted by Luis Guilherme Macena (guilhermelg2004@gmail.com) on 2013-04-08T16:55:05Z No. of bitstreams: 1 Laurinda Yoko Shinzato Higa_TESE.pdf: 1486069 bytes, checksum: f70375f751ecd6d4742cf70048bbdb2e (MD5) / Made available in DSpace on 2013-04-08T16:55:05Z (GMT). No. of bitstreams: 1 Laurinda Yoko Shinzato Higa_TESE.pdf: 1486069 bytes, checksum: f70375f751ecd6d4742cf70048bbdb2e (MD5) Previous issue date: 2011 / Fundação Oswaldo Cruz. Instituto Fernandes Figueira. Departamento de Ensino. Programa de Pós-Graduação em Saúde da Criança e da Mulher. Rio de Janeiro, RJ, Brasil / Introdução: A fibrose cística (FC) é uma doença genética, de transmissão autossômica recessiva, que compromete múltiplos órgãos, que apresenta curso crônico e progressivo sendo considerada potencialmente letal. Objetivos: Estimar a sobrevivência dos pacientes com FC e os fatores de risco associados à redução no tempo de sobrevivência. Métodos: Tratou-se de uma coorte aberta de casos diagnosticados entre 01/01/1990 e 10/10/2009 no Centro de Referência em FC do RJ, CRFC-RJ, Brasil na qual se analisou a sobrevivência global e fatores de risco associados com a sobrevida dos pacientes. O período de risco iniciou-se na idade ao diagnóstico e terminou na idade quando ocorreu o óbito por FC, a perda de seguimento ou o fim do estudo. Os fatores analisados foram: sexo, motivo da suspeita diagnóstica, genótipo, número de órgãos comprometidos, estado nutricional, colonização bacteriana, reposição enzimática e década do diagnóstico. As curvas de sobrevivência foram estimadas pelo método Kaplan- Meier, ajustadas para truncamento à esquerda e para dados censurados à direita. A seguir, as hazard ratios (HR) foram estimadas pelo modelo de Cox, utilizando o processo de contagem, tendo a idade como escala de tempo e avaliadas pelo teste de razão de verossimilhança, e os modelos comparados pela análise de resíduos. Resultados: A população (n=177) apresentou o predomínio do sexo feminino (56%) e a idade mediana ao diagnóstico foi 14 meses. A idade mediana de sobrevivência foi 20,8 anos. Após o diagnóstico 81% sobreviveram até cinco anos; 70% até 10 anos e 61% até 14,5 anos. O modelo explicou 19,9% dos efeitos e incluiu seis covariáveis: colonização por Pseudomonas aeruginosa, isolada e associada (HR = 10,30; IC95% = 2,41-43,97), por Staphylococcus aureus (HR=4,50; IC95% = 0,93-1,85), por outras bactérias (HR=3,38; IC95% = 0,92-1,32), sexo feminino (HR=1,95; IC95% = 0,96-3,96), estado nutricional ≤ p5 (HR=1,94; IC95% = 0,94-3,98) e diagnóstico na década de 1990 (HR=4,34; IC95% = 1,50-12,52). Conclusão: Este estudo de coorte de 177 pacientes com FC mostrou uma idade mediana de sobrevivência de 20,8 anos dos pacientes no CRFC-RJ. Foram confirmados os efeitos das covariáveis que, presentes ao diagnóstico, se associaram a maior mortalidade. A intervenção nestas covariáveis promoverá a recuperação nutricional, a erradicação da Pseudomonas aeruginosa ou o adiamento da colonização crônica, dessa forma aumentando a sobrevivência. / Introduction: Cystic Fibrosis (CF) is a rare genetic disease, of autossomal recessive transmission, with multiple organ involvement, progressive course and potentially lethal. Objective: To study the CF patients survival and to find the factors associated with. Methods: In an open cohort of cases diagnosed between 01/01/1990 and 10/10/2009 in a CF reference center in Rio de Janeiro, we analyzed global survival and risk factors associated with the survival of CF patients. The at-risk period started at the age of CF diagnosis and ended at age of death, loss of follow-up or end of the study. The factors analyzed were gender, presentation mode, genotype, number of involved organs, nutritional state, bacterial colonization, enzyme replacement and decade of diagnosis. Survival curves were estimated by Kaplan-Meier (KM) adjusted for left truncation and right censored data. Hazard ratios (HR) were estimated by Cox model using counting process approach with age as time scale and evaluated by likelihood ratio test. Model diagnostic was conducted by residuals analysis. Results: The majority of the population (n=177) was female (56%) and during the study the median age at diagnosis was 14 months. The median survival was of 20.8 years. After diagnosis, 81% survived up to 5 years, 70% up to 10 and 61% up to 14.5. The model explained 19.9% of the effects and included six covariates: Pseudomonas aeruginosa colonization, isolated or associated (HR = 10.30; 95%CI = 2.41-43.97), for Staphylococcus aureus (HR = 4.50; CI95% = 0.93-1.85), for other bacteria (HR = 3.38; CI95% = 0.92-1.32), for female gender (HR = 1.95; CI95% = 0.96-3.96), for nutritional state ≤ p5 (HR = 1.94; CI95% = 0.94-3.98), and for diagnostic decade (HR = 4.34; CI95% = 1.50-12.52). Conclusion: The strength of risk factors found at diagnosis was evident in the prognosis besides indicating that interventions may reduce morbidity by nutritional recovery and by Pseudomonas aeruginosa eradication thus increasing survival.

Background: Data on the impact of gender on mortality after radical cystectomy is conflicting. We investigated a large single center sample with long-term follow-up in order to determine the relationship between gender and outcome. Patients and Methods: A total of 1,184 consecutive patients who underwent radical cystectomy for high risk superficial or muscle-invasive urothelial or undifferentiated bladder cancer between 1993 and 2015 were stratified by gender. Demographic data was compared using Mann-Whitney U test, chi-square test, or Fisher exact test. Cox proportional hazard models were used for the analysis of competing risks and logit models were used for the prediction of the receipt of adjuvant cisplatin-based chemotherapy. Results: Female patients were older, healthier, less frequently current smokers and had more extravesical tumors. In the multivariate analyses, female gender was an independent predictor of (lower) non-bladder cancer (competing) mortality (hazards ratio [HR] 0.68, 95% CI 0.49–0.95, p = 0.0248) but no predictor of bladder cancer-specific mortality (HR in the full model 1.20, 95% CI 0.94–1.54, p = 0.15). Gender was no predictor of the receipt of adjuvant cisplatin-based chemotherapy. Conclusions: Female gender was associated with an increased risk of extravesical disease but was no independent predictor of bladder cancer-specific mortality. Anatomical differences might be a plausible explanation for these observations.

Denna uppsats har undersökt tid-till-försäljning på Uppsala kommuns bostadsmarknad för lägenheter under året 2021. För att analysera tid-till-försäljning har metoder från överlevnadsanalys använts. Överlevnadsfunktionen och den kumulativa hasardfunktionen har skattats med Kaplan-Meier-skattningen och Nelson-Aalen-skattningen. Därutöver har tre modeller skattats; en Cox proportionell hasardmodell och två 'Accelerated Failure Time'-modeller varav en var en Weibullmodell och en var en Loglogistiskmodell. Resultaten indikerar att tid-till-försäljning har en hög hasard efter två veckor på marknaden varefter en avtagande hasard. Resultaten indikerar att kovariat har en statistisk signifikant effekt på tid-till-försäljning. Grafiska tester indikerar att antagandet om proportionalitet för Cox proportionella hasardmodell och antagandet om den underliggande hasardfunktionen för Weibullmodellen är orimliga. Antagandet om den underliggande hasardfunktionen för loglogistiskamodellen verkar rimlig. Goodness-of-fit indikerar att Weibullmodellen och loglogistiskamodellen var mer välanpassade till datamaterialet än Cox proportionella hasardmodell. / This bachelor's thesis has investigated time-to-sale on the Uppsala municipality property market for apartments during 2021. Analysis has been performed utilising methods from survival analysis. Both the survival function and cumulative hazard function were estimated using the Kaplan-Meier estimate and the Nelson-Aalen estimate respectively. Furthermore, three models were estimated; a Cox Proportional Hazards model as well as two Accelerated Failure Time models of which one was a Weibullmodell and the other was a loglogistic model. The results indicate that time-to-sale has a high hazard after two weeks on the market followed by a decreasing hazard. The results also indicate that covariates have a statistically significant effect on time-to-sale. Graphical tests indicate that the assumption of proportionality for the Cox Proportional Hazards model and the assumption of the underlying hazard function for the Weibullmodell are unreasonable. The assumed hazardfunction of the loglogistic model was found to be reasonable. Goodness of fit indicates that the Weibull model and loglogistic model were a better fit to the data than the Cox proportional Hazardsmodel.

Introduction/Background: Guidelines from the World Health Organization currently recommend targeting a body mass index (BMI) between 18.5 and 24.9 kg/m2 based on the lowest risk of mortality observed in epidemiological studies. However, these recommendations are based on population observations and do not take into account potential inter-individual differences. We hypothesized that genetic and non-genetic differences in adiposity, anthropometric, and metabolic measures result in inter-individual variation in the optimal BMI. Methods: Genetic variants associated with BMI as well as related adiposity, anthropometric, and metabolic phenotypes (e.g. triglyceride (TG)) were combined into polygenic risk scores (PRS), cumulative risk scores derived from the weighted contributions of each variant. 387,692 participants in the UK Biobank were split by quantiles of PRS or clinical biomarkers such as C-reactive protein (CRP), and alanine aminotransferase (ALT). The BMI linked with the lowest risk of all-cause and cause-specific mortality outcomes (“nadir value”) was then compared across quantiles (“Cox meta-regression model”). Our results were replicated using the non-linear mendelian randomization (NLMR) model to assess causality. Results: The nadir value for the BMI–all-cause mortality relationship differed across percentiles of BMI PRS, suggesting inter-individual variation in optimal BMI based on genetics (p = 0.005). There was a difference of 1.90 kg/m2 in predicted optimal BMI between individuals in the top and bottom 5th BMI PRS percentile. Individuals having above and below median TG (p = 1.29×10-4), CRP (p = 7.92 × 10-5), and ALT (p = 2.70 × 10-8) levels differed in nadir for this relationship. There was no difference in the computed nadir between the Cox meta-regression or NLMR models (p = 0.102). Conclusions: The impact of BMI on mortality is heterogenous due to individual genetic and clinical biomarker level differences. Although we cannot confirm that are results are causal, genetics and clinical biomarkers have potential use for making more tailored BMI recommendations for patients. / Thesis / Master of Science (MSc) / The World Health Organization (WHO) recommends targeting a body mass index (BMI) between 18.5 - 24.9 kg/m2 for optimal health. However, this recommendation does not take into account individual differences in genetics or biology. Our project aimed to determine whether the optimal BMI, or the BMI associated with the lowest risk of mortality, varies due to genetic or biological variation. Analyses were conducted across 387,692 individuals. We divided participants into groups according to genetic risk for obesity or clinical biomarker profile. Our results show that the optimal BMI varies according to genetic or biomarker profile. WHO recommendations do not account for this variation, as the optimal BMI can fall under the normal 18.5 - 24.9 kg/m2 or overweight 25.0 – 29.0 kg/m2 WHO BMI categories depending on individual genetic or biomarker profile. Thus, there is potential for using genetic and/or biomarker profiles to make more precise BMI recommendations for patients.

The thesis investigates the impact of age-biased sampling on the accuracy of lifetime prediction models for traffic signs. The bias in question originates from age-biased sampling as a result of the inspection paradox. This phenomenon occurs because longer intervals have a higher probability of being observed compared to shorter intervals, leading to a skewed representation in the data. The research employs a dual approach: firstly, conducting an extensive analysis of real data on traffic sign longevity using a Weibull Survival Model. This analysis is based on the data set compiled by Saleh et al., (2023). Secondly, the study sets up a Monte Carlo simulation to systematically explore the effects of varying degrees and patterns of age bias on the sample. The simulation parameters are derived from the original Weibull Model parameters, obtained from the real dataset. This approach ensures that the simulations closely replicate the actual parameters and estimates. The comparison of the true shape, scale, intercept, and the coefficients associated with the covariates against the simulated estimates indicates a significant bias in the dataset. The study also examines the impact of this bias on the predictive capabilities of various models: Weibull Modeling, Cox Proportional Hazards, Kaplan Meier, and Random Survival Forest. This is done by comparing the true means and medians of the simulated data with the estimates from each model. The findings show that all models exhibit large deviations from the actual means and medians at varying bias levels in the simulated data. The accuracy of the predictions is measured using the Brier Score. This score also shows significant deviations from the prediction accuracy of the original Weibull Model applied to the real dataset, especially when the bias levels vary across simulated datasets. Given these findings, the study advises against using the aforementioned methods for lifetime modeling of traffic signs when there is age bias due to the inspection paradox.

Com o objetivo de avaliar o atendimento dos pacientes submetidos à intervenção cirúrgica cardiovascular no protocolo de atendimento na via rápida (fast track recovery) em relação ao protocolo convencional, foi comparada a movimentação dos pacientes atendidos em ambos os protocolos nas diferentes unidades hospitalares. O estudo foi realizado em hospital público universitário especializado em cardiologia de 400 leitos, de referência terciária para o Sistema Único de Saúde. Foram estudados 175 pacientes, 107 (61%) homens e 68 (39%) mulheres, de idades entre 2 meses a 81 anos, dos quais 107 operados no protocolo da via rápida e 68 no protocolo convencional. Foram avaliadas variáveis demográficas, clínicas e, para avaliar a movimentação dos pacientes nas diferentes unidades hospitalares, as taxas de alta por unidade de tempo em cada unidade. A análise estatística foi feita por meio de análise exploratória, método de Kaplan Meier e modelo de riscos proporcionais de Cox. A análise de variância foi empregada para comparar o faturamento das despesas. A taxa de alta das diferentes unidades hospitalares por unidade de tempo dos portadores de cardiopatia congênita atendidos no protocolo da via rápida em relação ao protocolo da via convencional foi: a) 11,3 vezes a taxa de alta quando assistidos no protocolo na via convencional quanto ao tempo de permanência no centro cirúrgico; b) 6,3 vezes quanto à duração da intervenção cirúrgica; c) 6,8 vezes quanto à duração da anestesia; d) 1,5 vezes quanto à duração da perfusão; e) 2,8 vezes quanto à permanência na unidade de recuperação pós-operatória I; f) 6,7 vezes quanto à duração da hospitalização; g) 2,8 vezes quanto à permanência na unidade de internação pré-operatória; h) 2,1 vezes quanto à permanência na unidade de internação após a alta da unidade de terapia intensiva de recuperação pós-operatória. Para os portadores de cardiopatia isquêmica, as taxas de alta das unidades hospitalares para os protocolos de atendimento no protocolo da via rápida e no protocolo convencional não demonstraram diferença estatisticamente significante. Os valores de faturamento das despesas de internação dos portadores de cardiopatia congênita decorrentes de exames e procedimentos realizados nas fases pré- e pós-operatória e dos exames da fase trans-operatória foram menores quando os pacientes foram assistidos no protocolo da via rápida. Portanto, os portadores de cardiopatias congênita apresentaram menor permanência hospitalar nos recursos médicos hospitalares instalados, quando assistidos no protocolo de atendimento na via rápida, bem como menores despesas nas fases pré- e pós- operatória da internação. / Objective - To evaluate patient assistance in pre, per and postoperative phases of cardiac surgical intervention under fast track recovering protocol compared to the conventional way. Patients - 175 patients were studied, 107 (61%) men and 68 (39%) women. Ages 2 months to 81 years old. Patients included: first surgical intervention, congenital and ischemic cardiopathy without complexity, normal ventricular function and with at least 2 preoperative ambulatory consultations. Patients submitted to emergency surgeries were excluded. Interventions - assistance submitted by fast track and conventional protocol. Statistical analysis (measures) - exploratory, uni-varied (Kaplan Meier) and multi-varied (Cox) of the time in each admission unit. Hospital installations were classified in ambulatory, preoperative admission unit, surgical center, postoperative recovery unit and postoperative admission unit; the expression of this use was the discharge rate by unit of time from the significant interaction observed between assistance protocol and the kind of cardiopathy for the stay in the surgical center, surgical intervention time, stay in postoperative recovery unit, anesthesia time and time between admission and surgery dates. Results - the patients of congenital cardiopathy who underwent the protocol of conventional way recovery in relation to the fast track protocol, in the reliability range of 95% allows one to state that discharge rate by unit of time of the congenital cardiopathy patients assisted by the fast track protocol was: 11.3 times the discharge rate when assisted by the conventional way protocol as to the time of staying in the surgical center; 6.3 times as to the duration of the surgical intervention; 6.8 times as to duration of the anesthesia; 1.5 times as to the duration of the perfusion; 2.8 times as to the stay in the postoperative recovery unit; 6.7 times as to the stay in the hospital (period of time between the admission and the discharge date); 2.8 times as to the stay in the preoperative admission unit ( period of time between the admission date and the surgery date); 2.1 times as to the stay in the postoperative unit (period of time between the date of leaving the postoperative recovery unit and the date of discharge from the hospital). For the ischemia cardiopathy patients the risks concerning the protocols of recovery by the traditional way and the fast track were the same. CONCLUSIONS - The data concerning this study allows one to suggest that the assistance can be more efficient if one takes into consideration some variables studied in the protocol of fast track recovery. The congenital and ischemic cardiopathy patients presented shorter interval of time (concerning hospital stay in doctor-hospital installed facilities) when assisted in the fast track recovery protocol as well as fewer expenses with medical and hospital assistance.

Le fonctionnement d'un système, de façon générale, peut être affecté par un incident imprévu. Lorsque cet incident a de lourdes conséquences tant sur l'intégrité du système que sur la qualité de ses produits, on dit alors qu'il se situe dans le cadre des événements dits extrêmes. Ainsi, de plus en plus les chercheurs portent un intérêt particulier à la modélisation des événements extrêmes pour diverses études telles que la fiabilité des systèmes et la prédiction des différents risques pouvant entraver le bon fonctionnement d'un système en général. C'est dans cette optique que s'inscrit la présente thèse. Nous utilisons la Théorie des Valeurs Extrêmes (TVE) et les statistiques d'ordre extrême comme outil d'aide à la décision dans la modélisation et la gestion des risques dans l'usinage et l'aviation. Plus précisément, nous modélisons la surface de rugosité de pièces usinées et la fiabilité de l'outil de coupe associé par les statistiques d'ordre extrême. Nous avons aussi fait une modélisation à l'aide de l'approche dite du "Peaks-Over Threshold, POT" permettant de faire des prédictions sur les éventuelles victimes dans l'Aviation Générale Américaine (AGA) à la suite d'accidents extrêmes. Par ailleurs, la modélisation des systèmes soumis à des facteurs d'environnement ou covariables passent le plus souvent par les modèles à risque proportionnel basés sur la fonction de risque. Dans les modèles à risque proportionnel, la fonction de risque de base est généralement de type Weibull, qui est une fonction monotone; l'analyse du fonctionnement de certains systèmes comme l'outil de coupe dans l'industrie a montré qu'un système peut avoir un mauvais fonctionnement sur une phase et s'améliorer sur la phase suivante. De ce fait, des modifications ont été apportées à la distribution de Weibull afin d'avoir des fonctions de risque de base non monotones, plus particulièrement les fonctions de risque croissantes puis décroissantes. En dépit de ces modifications, la prise en compte des conditions d'opérations extrêmes et la surestimation des risques s'avèrent problématiques. Nous avons donc, à partir de la loi standard de Gumbel, proposé une fonction de risque de base croissante puis décroissante permettant de prendre en compte les conditions extrêmes d'opérations, puis établi les preuves mathématiques y afférant. En outre, un exemple d'application dans le domaine de l'industrie a été proposé. Cette thèse est divisée en quatre chapitres auxquels s'ajoutent une introduction et une conclusion générales. Dans le premier chapitre, nous rappelons quelques notions de base sur la théorie des valeurs extrêmes. Le deuxième chapitre s'intéresse aux concepts de base de l'analyse de survie, particulièrement à ceux relatifs à l'analyse de fiabilité, en proposant une fonction de risque croissante-décroissante dans le modèle à risques proportionnels. En ce qui concerne le troisième chapitre, il porte sur l'utilisation des statistiques d'ordre extrême dans l'usinage, notamment dans la détection de pièces défectueuses par lots, la fiabilité de l'outil de coupe et la modélisation des meilleures surfaces de rugosité. Le dernier chapitre porte sur la prédiction d'éventuelles victimes dans l'Aviation Générale Américaine à partir des données historiques en utilisant l'approche "Peaks-Over Threshold" / The operation of a system in general may at any time be affected by an unforeseen incident. When this incident has major consequences on the system integrity and the quality of system products, then it is said to be in the context of extreme events. Thus, increasingly researchers have a particular interest in modeling such events with studies on the reliability of systems and the prediction of the different risks that can hinder the proper functioning of a system. This thesis takes place in this very perspective. We use Extreme Value Theory (EVT) and extreme order statistics as a decision support tool in modeling and risk management in industry and aviation. Specifically, we model the surface roughness of machined parts and the reliability of the associated cutting tool with the extreme order statistics. We also did a modeling using the "Peaks-Over Threshold, POT" approach to make predictions about the potential victims in the American General Aviation (AGA) following extreme accidents. In addition, the modeling of systems subjected to environmental factors or covariates is most often carried out by proportional hazard models based on the hazard function. In proportional hazard models, the baseline risk function is typically Weibull distribution, which is a monotonic function. The analysis of the operation of some systems like the cutting tool in the industry has shown that a system can deteriorated on one phase and improving on the next phase. Hence, some modifications have been made in the Weibull distribution in order to have non-monotonic basic risk functions, more specifically, the increasing-decreasing risk function. Despite these changes, taking into account extreme operating conditions and overestimating risks are problematics. We have therefore proposed from Gumbel's standard distribution, an increasingdecreasing risk function to take into account extreme conditions, and established mathematical proofs. Furthermore, an example of the application in the field of industry was proposed. This thesis is organized in four chapters and to this must be added a general introduction and a general conclusion. In the first chapter, we recall some basic notions about the Extreme Values Theory. The second chapter focuses on the basic concepts of survival analysis, particularly those relating to reliability analysis by proposing a function of increasing-decreasing hazard function in the proportional hazard model. Regarding the third chapter, it deals with the use of extreme order statistics in industry, particularly in the detection of defective parts, the reliability of the cutting tool and the modeling of the best roughness surfaces. The last chapter focuses on the prediction of potential victims in AGA from historical data using the Peaks-Over Threshold approach.

No description available.