925 resultados para Hierarchical logistic model
Resumo:
The main objective of this study was to develop and validate a computer-based statistical algorithm based on a multivariable logistic model that can be translated into a simple scoring system in order to ascertain stroke cases using hospital admission medical records data. This algorithm, the Risk Index Score (RISc), was developed using data collected prospectively by the Brain Attack Surveillance in Corpus Christ (BASIC) project. The validity of the RISc was evaluated by estimating the concordance of scoring system stroke ascertainment to stroke ascertainment accomplished by physician review of hospital admission records. The goal of this study was to develop a rapid, simple, efficient, and accurate method to ascertain the incidence of stroke from routine hospital admission hospital admission records for epidemiologic investigations. ^ The main objectives of this study were to develop and validate a computer-based statistical algorithm based on a multivariable logistic model that could be translated into a simple scoring system to ascertain stroke cases using hospital admission medical records data. (Abstract shortened by UMI.)^
Resumo:
Generalized linear Poisson and logistic regression models were utilized to examine the relationship between temperature and precipitation and cases of Saint Louis encephalitis virus spread in the Houston metropolitan area. The models were investigated with and without repeated measures, with a first order autoregressive (AR1) correlation structure used for the repeated measures model. The two types of Poisson regression models, with and without correlation structure, showed that a unit increase in temperature measured in degrees Fahrenheit increases the occurrence of the virus 1.7 times and a unit increase in precipitation measured in inches increases the occurrence of the virus 1.5 times. Logistic regression did not show these covariates to be significant as predictors for encephalitis activity in Houston for either correlation structure. This discrepancy for the logistic model could be attributed to the small data set.^ Keywords: Saint Louis Encephalitis; Generalized Linear Model; Poisson; Logistic; First Order Autoregressive; Temperature; Precipitation. ^
Resumo:
The study objectives were to determine risk factors for preterm labor (PTL) in Colorado Springs, CO, with emphasis on altitude and psychosocial factors, and to develop a model that identifies women at high risk for PTL. Three hundred and thirty patients with PTL were matched to 460 control patients without PTL using insurance category as an indirect measure of social class. Data were gathered by patient interview and review of medical records. Seven risk groups were compared: (1) Altitude change and travel; (2) Psychosocial ((a) child, sexual, spouse, alcohol and drug abuse; (b) neuroses and psychoses; (c) serious accidents and injuries; (d) broken home (maternal parental separation); (e) assault (physical and sexual); and (f) stress (emotional, domestic, occupational, financial and general)); (3) demographic; (4) maternal physical condition; (5) Prenatal care; (6) Behavioral risks; and (7) Medical factors. Analysis was by logistic regression. Results demonstrated altitude change before or after conception and travel during pregnancy to be non-significant, even after adjustment for potential confounding variables. Five significant psychosocial risk factors were determined: Maternal sex abuse (p = 0.006), physical assault (p = 0.025), nervous breakdown (p = 0.011), past occupational injury (p = 0.016), and occupational stress (p = 0.028). Considering all seven risk groups in the logistic regression, we chose a logistic model with 11 risk factors. Two risk factors were psychosocial (maternal spouse abuse and past occupational injury), 1 was pertinent to maternal physical condition ($\le$130 lbs. pre-pregnancy weight), 1 to prenatal care ($\le$10 prenatal care visits), 2 pertinent to behavioral risks ($>$15 cigarettes per day and $\le$30 lbs. weight gain) and 5 medical factors (abnormal genital culture, previous PTB, primiparity, vaginal bleeding and vaginal discharge). We conclude that altitude change is not a risk factor for PTL and that selected psychosocial factors are significant risk factors for PTL. ^
Resumo:
A case-control study has been conducted examining the relationship between preterm birth and occupational physical activity among U.S. Army enlisted gravidas from 1981 to 1984. The study includes 604 cases (37 or less weeks gestation) and 6,070 controls (greater than 37 weeks gestation) treated at U.S. Army medical treatment facilities worldwide. Occupational physical activity was measured using existing physical demand ratings of military occupational specialties.^ A statistically significant trend of preterm birth with increasing physical demand level was found (p = 0.0056). The relative risk point estimates for the two highest physical demand categories were statistically significant, RR's = 1.69 (p = 0.02) and 1.75 (p = 0.01), respectively. Six of eleven additional variables were also statistically significant predictors of preterm birth: age (less than 20), race (non-white), marital status (single, never married), paygrade (E1 - E3), length of military service (less than 2 years), and aptitude score (less than 100).^ Multivariate analyses using the logistic model resulted in three statistically significant risk factors for preterm birth: occupational physical demand; lower paygrade; and non-white race. Controlling for race and paygrade, the two highest physical demand categories were again statistically significant with relative risk point estimates of 1.56 and 1.70, respectively. The population attributable risk for military occupational physical demand was 26%, adjusted for paygrade and race; 17.5% of the preterm births were attributable to the two highest physical demand categories. ^
Resumo:
The relationship between serum cholesterol and cancer incidence was investigated in the population of the Hypertension Detection and Follow-up Program (HDFP). The HDFP was a multi-center trial designed to test the effectiveness of a stepped program of medication in reducing mortality associated with hypertension. Over 10,000 participants, ages 30-69, were followed with clinic and home visits for a minimum of five years. Cancer incidence was ascertained from existing study documents, which included hospitalization records, autopsy reports and death certificates. During the five years of follow-up, 286 new cancer cases were documented. The distribution of sites and total number of cases were similar to those predicted using rates from the Third National Cancer Survey. A non-fasting baseline serum cholesterol level was available for most participants. Age, sex, and race specific five-year cancer incidence rates were computed for each cholesterol quartile. Rates were also computed by smoking status, education status, and percent ideal weight quartiles. In addition, these and other factors were investigated with the use of the multiple logistic model.^ For all cancers combined, a significant inverse relationship existed between baseline serum cholesterol levels and cancer incidence. Previously documented associations between smoking, education and cancer were also demonstrated but did not account for the relationship between serum cholesterol and cancer. The relationship was more evident in males than females but this was felt to represent the different distribution of occurrence of specific cancer sites in the two sexes. The inverse relationship existed for all specific sites investigated (except breast) although a level of statistical significance was reached only for prostate carcinoma. Analyses after exclusion of cases diagnosed during the first two years of follow-up still yielded an inverse relationship. Life table analysis indicated that competing risks during the period of follow-up did not account for the existence of an inverse relationship. It is concluded that a weak inverse relationship does exist between serum cholesterol for many but not all cancer sites. This relationship is not due to confounding by other known cancer risk factors, competing risks or persons entering the study with undiagnosed cancer. Not enough information is available at the present time to determine whether this relationship is causal and further research is suggested. ^
Resumo:
My dissertation focuses mainly on Bayesian adaptive designs for phase I and phase II clinical trials. It includes three specific topics: (1) proposing a novel two-dimensional dose-finding algorithm for biological agents, (2) developing Bayesian adaptive screening designs to provide more efficient and ethical clinical trials, and (3) incorporating missing late-onset responses to make an early stopping decision. Treating patients with novel biological agents is becoming a leading trend in oncology. Unlike cytotoxic agents, for which toxicity and efficacy monotonically increase with dose, biological agents may exhibit non-monotonic patterns in their dose-response relationships. Using a trial with two biological agents as an example, we propose a phase I/II trial design to identify the biologically optimal dose combination (BODC), which is defined as the dose combination of the two agents with the highest efficacy and tolerable toxicity. A change-point model is used to reflect the fact that the dose-toxicity surface of the combinational agents may plateau at higher dose levels, and a flexible logistic model is proposed to accommodate the possible non-monotonic pattern for the dose-efficacy relationship. During the trial, we continuously update the posterior estimates of toxicity and efficacy and assign patients to the most appropriate dose combination. We propose a novel dose-finding algorithm to encourage sufficient exploration of untried dose combinations in the two-dimensional space. Extensive simulation studies show that the proposed design has desirable operating characteristics in identifying the BODC under various patterns of dose-toxicity and dose-efficacy relationships. Trials of combination therapies for the treatment of cancer are playing an increasingly important role in the battle against this disease. To more efficiently handle the large number of combination therapies that must be tested, we propose a novel Bayesian phase II adaptive screening design to simultaneously select among possible treatment combinations involving multiple agents. Our design is based on formulating the selection procedure as a Bayesian hypothesis testing problem in which the superiority of each treatment combination is equated to a single hypothesis. During the trial conduct, we use the current values of the posterior probabilities of all hypotheses to adaptively allocate patients to treatment combinations. Simulation studies show that the proposed design substantially outperforms the conventional multi-arm balanced factorial trial design. The proposed design yields a significantly higher probability for selecting the best treatment while at the same time allocating substantially more patients to efficacious treatments. The proposed design is most appropriate for the trials combining multiple agents and screening out the efficacious combination to be further investigated. The proposed Bayesian adaptive phase II screening design substantially outperformed the conventional complete factorial design. Our design allocates more patients to better treatments while at the same time providing higher power to identify the best treatment at the end of the trial. Phase II trial studies usually are single-arm trials which are conducted to test the efficacy of experimental agents and decide whether agents are promising to be sent to phase III trials. Interim monitoring is employed to stop the trial early for futility to avoid assigning unacceptable number of patients to inferior treatments. We propose a Bayesian single-arm phase II design with continuous monitoring for estimating the response rate of the experimental drug. To address the issue of late-onset responses, we use a piece-wise exponential model to estimate the hazard function of time to response data and handle the missing responses using the multiple imputation approach. We evaluate the operating characteristics of the proposed method through extensive simulation studies. We show that the proposed method reduces the total length of the trial duration and yields desirable operating characteristics for different physician-specified lower bounds of response rate with different true response rates.
Resumo:
This paper estimates the impact of industrial agglomeration on firm-level productivity in Chinese manufacturing sectors. To account for spatial autocorrelation across regions, we formulate a hierarchical spatial model at the firm level and develop a Bayesian estimation algorithm. A Bayesian instrumental-variables approach is used to address endogeneity bias of agglomeration. Robust to these potential biases, we find that agglomeration of the same industry (i.e. localization) has a productivity-boosting effect, but agglomeration of urban population (i.e. urbanization) has no such effects. Additionally, the localization effects increase with educational levels of employees and the share of intermediate inputs in gross output. These results may suggest that agglomeration externalities occur through knowledge spillovers and input sharing among firms producing similar manufactures.
Resumo:
Objective The neurodevelopmental–neurodegenerative debate is a basic issue in the field of the neuropathological basis of schizophrenia (SCH). Neurophysiological techniques have been scarcely involved in such debate, but nonlinear analysis methods may contribute to it. Methods Fifteen patients (age range 23–42 years) matching DSM IV-TR criteria for SCH, and 15 sex- and age-matched control subjects (age range 23–42 years) underwent a resting-state magnetoencephalographic evaluation and Lempel–Ziv complexity (LZC) scores were calculated. Results Regression analyses indicated that LZC values were strongly dependent on age. Complexity scores increased as a function of age in controls, while SCH patients exhibited a progressive reduction of LZC values. A logistic model including LZC scores, age and the interaction of both variables allowed the classification of patients and controls with high sensitivity and specificity. Conclusions Results demonstrated that SCH patients failed to follow the “normal” process of complexity increase as a function of age. In addition, SCH patients exhibited a significant reduction of complexity scores as a function of age, thus paralleling the pattern observed in neurodegenerative diseases. Significance Our results support the notion of a progressive defect in SCH, which does not contradict the existence of a basic neurodevelopmental alteration. Highlights ► Schizophrenic patients show higher complexity values as compared to controls. ► Schizophrenic patients showed a tendency to reduced complexity values as a function of age while controls showed the opposite tendency. ► The tendency observed in schizophrenic patients parallels the tendency observed in Alzheimer disease patients.
Resumo:
A software for simulation of bruise occurrence in fruit grading lines, SIMLIN 2.0, is presented. Examples of application are included on the simulation of handling Sudanell peaches. SIMLIN 2.0 provides algorithms for the selection of logistic bruise prediction models adjusted on the basis of user designed laboratory tests. Handled fruits are characterised for simulation by means of statistical features on the independent variables of the logistic model. SIMLIN 2.0 allows to display different line designs establishing their aggressiveness from internal data bases. Aggressiveness is characterised in terms of data gathered with electronic products IS-100 type. The software provides graphical outputs which enable decision making on the improvement strategies of the lines and the selection of the product to be handled.
Resumo:
El WCTR es un congreso de reconocido prestigio internacional en el ámbito de la investigación del transporte y aunque las actas publicadas están en formato digital y sin ISSN ni ISBN, lo consideramos lo suficientemente importante como para que se considere en los indicadores. This paper aims at describing how multilateral cooperation policies are influencing national transport policies in developing countries. It considers the evolution of national transport policies and institutional frameworks in Algeria, Morocco and Tunisia in the last 10 years, and analyses the influence that EU cooperation programmes (particularly those within the Euromed programme initiative) and international coordination activities have played in the evolution towards efficient, sustainable transport systems in those countries. Notwithstanding the significant socioeconomic, political and institutional differences among the three countries, three major traits are common to the transport policy framework in all cases: a focus on megaprojects; substitution of traditional ministerial services by ad hoc public agencies to develop those megaprojects, and progressive involvement of international private players for the operation (and eventually the design and construction) of new projects, focusing on know-how transfer rather than investment needs. The hypotheses is that these similarities are largely due to the influence of the international cooperation promoted by the European Union since the mid- 1990s. The new decision making situation is characterized by the involvement of two new relevant stakeholders, the EU and a limited number of global transport operators. The hierarchical governance model evolves towards more complex structures, which explain the three common traits mentioned above. International coordination has been crucial for developing national transport visions, which are coherent with a regional, transnational system.
Resumo:
An extension of guarantees related to rainfall-related risks in the insurance of processing tomato crops has been accompanied with a large increase in claims in Western Spain, suggesting that damages may have been underestimated in previous years. A database was built by linking agricultural insurance records, meteorological data from local weather stations, and topographic data. The risk of rainfall-related damages in processing tomato in the Extremenian Guadiana river basin (W Spain) was studied using a logistic model. Risks during the growth of the crop and at harvesting were modelled separately. First, the risk related to rainfall was modelled as a function of meteorological, terrain and management variables. The resulting models were used to identify the variables responsible for rainfall-related damages, with a view to assess the potential impact of extending insurance coverage, and to develop an index to express the suitability of the cropping system for insurance. The analyses reveal that damages at different stages of crop development correspond to different hazards. The geographic dependence of the risk influences the scale at which the model might have validity, which together with the year dependency, the possibility of implementing index based insurances is questioned.
Resumo:
El planteamiento tradicional de análisis de la accidentalidad en carretera pasa por la consideración de herramientas paliativas, como son la identificación y gestión de los puntos negros o tramos de concentración de accidentes, o preventivas, como las auditorías e inspecciones de seguridad vial. En esta tesis doctoral se presenta un planteamiento complementario a estas herramientas, desde una perspectiva novedosa: la consideración de los tramos donde no se producen accidentes; son los denominados Tramos Blancos. La tesis persigue demostrar que existen determinados parámetros del diseño de las carreteras y del tráfico que, bajo características generales similares de las vías, tienen influencia en el hecho de que se produzcan o no accidentes, adicionalmente a la exposición al riesgo, como factor principal, y a otros factores. La propia definición de los Tramos Blancos, entendidos como tramos de carreteras de longitud representativa donde no se han producido accidentes con víctimas mortales o heridos graves durante un periodo largo de tiempo, garantiza que esta situación no se produzca como consecuencia de la aleatoriedad de los accidentes, sino que pudiera deberse a una confluencia específica de determinados parámetros de la geometría de la vía y del tráfico total y de vehículos pesados. Para el desarrollo de esta investigación se han considerado la red de autopistas de peaje y las carreteras convencionales de la Red del Estado de España, que supone un total de 17.000 kilómetros, y los datos de accidentes con víctimas mortales y heridos graves en el periodo 2006-2010, ambos incluidos, en estas redes (un total de 10.000 accidentes). La red viaria objeto de análisis supone el 65% de la longitud de la Red de Carreteras del Estado, por la que circula el 33% de su tráfico; en ella se produjeron en el año 2013 el 47% de los accidentes con víctimas y el 60% de las víctimas mortales de la Red de Carreteras del Estado. Durante la investigación se ha desarrollado una base de datos de 250.130 registros y más de 3.5 millones de datos en el caso de las autopistas de peaje de la Red de Carreteras del Estado y de 935.402 registros y más de 14 millones de datos en el caso de la red convencional del Estado analizada. Tanto las autopistas de peaje como las carreteras convencionales han sido clasificadas según sus características de tráfico, de manera que se valoren vías con nivel de exposición al riesgo similar. Para cada tipología de vía, se ha definido como longitud de referencia para que un tramo se considere Tramo Blanco la longitud igual al percentil 95 de las longitudes de tramos sin accidentes con heridos graves o víctimas mortales durante el periodo 2006-2010. En el caso de las autopistas de peaje, en la tipología que ha sido considerada para la definición del modelo, esta longitud de referencia se estableció en 14.5 kilómetros, mientras que en el caso de las carreteras convencionales, se estableció en 7.75 kilómetros. Para cada uno de los tipos de vía considerados se han construido una base de datos en la que se han incluido las variables de existencia o no de Tramo Blanco, así como las variables de tráfico (intensidad media diaria total, intensidad de vehículos pesados y porcentaje de vehículos pesados ), la velocidad media y las variables de geometría (número de carriles, ancho de carril, ancho de arcén derecho e izquierdo, ancho de calzada y plataforma, radio, peralte, pendiente y visibilidad directa e inversa en los casos disponibles); como variables adicionales, se han incluido el número de accidentes con víctimas, los fallecidos y heridos graves, índices de peligrosidad, índices de mortalidad y exposición al riesgo. Los trabajos desarrollados para explicar la presencia de Tramos Blancos en la red de autopistas de peaje han permitido establecer las diferencias entre los valores medios de las variables de tráfico y diseño geométrico en Tramos Blancos respecto a tramos no blancos y comprobar que estas diferencias son significativas. Así mismo, se ha podido calibrar un modelo de regresión logística que explica parcialmente la existencia de Tramos Blancos, para rangos de tráfico inferiores a 10.000 vehículos diarios y para tráficos entre 10.000 y 15.000 vehículos diarios. Para el primer grupo (menos de 10.000 vehículos al día), las variables que han demostrado tener una mayor influencia en la existencia de Tramo Blanco son la velocidad media de circulación, el ancho de carril, el ancho de arcén izquierdo y el porcentaje de vehículos pesados. Para el segundo grupo (entre 10.000 y 15.000 vehículos al día), las variables independientes más influyentes en la existencia de Tramo Blanco han sido la velocidad de circulación, el ancho de calzada y el porcentaje de vehículos pesados. En el caso de las carreteras convencionales, los diferentes análisis realizados no han permitido identificar un modelo que consiga una buena clasificación de los Tramos Blancos. Aun así, se puede afirmar que los valores medios de las variables de intensidad de tráfico, radio, visibilidad, peralte y pendiente presentan diferencias significativas en los Tramos Blancos respecto a los no blancos, que varían en función de la intensidad de tráfico. Los resultados obtenidos deben considerarse como la conclusión de un análisis preliminar, dado que existen otros parámetros, tanto de diseño de la vía como de la circulación, el entorno, el factor humano o el vehículo que podrían tener una influencia en el hecho que se analiza, y no se han considerado por no disponer de esta información. En esta misma línea, el análisis de las circunstancias que rodean al viaje que el usuario de la vía realiza, su tipología y motivación es una fuente de información de interés de la que no se tienen datos y que permitiría mejorar el análisis de accidentalidad en general, y en particular el de esta investigación. Adicionalmente, se reconocen limitaciones en el desarrollo de esta investigación, en las que sería preciso profundizar en el futuro, reconociendo así nuevas líneas de investigación de interés. The traditional approach to road accidents analysis has been based in the use of palliative tools, such as black spot (or road sections) identification and management, or preventive tools, such as road safety audits and inspections. This thesis shows a complementary approach to the existing tools, from a new perspective: the consideration of road sections where no accidents have occurred; these are the so-called White Road Sections. The aim of this thesis is to show that there are certain design parameters and traffic characteristics which, under similar circumstances for roads, have influence in the fact that accidents occur, in addition to the main factor, which is the risk exposure, and others. White Road Sections, defined as road sections of a representative length, where no fatal accidents or accidents involving serious injured have happened during a long period of time, should not be a product of randomness of accidents; on the contrary, they might be the consequence of a confluence of specific parameters of road geometry, traffic volumes and heavy vehicles traffic volumes. For this research, the toll motorway network and single-carriageway network of the Spanish National Road Network have been considered, which is a total of 17.000 kilometers; fatal accidents and those involving serious injured from the period 2006-2010 have been considered (a total number of 10.000 accidents). The road network covered means 65% of the total length of the National Road Network, which allocates 33% of traffic volume; 47% of accidents with victims and 60% of fatalities happened in these road networks during 2013. During the research, a database of 250.130 registers and more than 3.5 million data for toll motorways and 935.042 registers and more than 14 million data for single carriageways of the National Road Network was developed. Both toll motorways and single-carriageways have been classified according to their traffic characteristics, so that the analysis is performed over roads with similar risk exposure. For each road type, a reference length for White Road Section has been defined, as the 95 percentile of all road sections lengths without accidents (with fatalities or serious injured) for 2006-2010. For toll motorways, this reference length concluded to be 14.5 kilometers, while for single-carriageways, it was defined as 7.75 kilometers. A detailed database was developed for each type of road, including the variable “existence of White Road Section”, as well as variables of traffic (average daily traffic volume, heavy vehicles average daily traffic and percentage of heavy vehicles from the total traffic volume), average speed and geometry variables (number of lanes, width of lane, width of shoulders, carriageway width, platform width, radius, superelevation, slope and visibility); additional variables, such as number of accidents with victims, number of fatalities or serious injured, risk and fatality rates and risk exposure, have also been included. Research conducted for the explanation of the presence of White Road Sections in the toll motorway network have shown statistically significant differences in the average values of variables of traffic and geometric design in White Road Sections compared with other road sections. In addition, a binary logistic model for the partial explanation of the presence of White Road Sections was developed, for traffic volumes lower than 10.000 daily vehicles and for those running from 10.000 to 15.000 daily vehicles. For the first group, the most influent variables for the presence of White Road Sections were the average speed, width of lane, width of left shoulder and percentage of heavy vehicles. For the second group, the most influent variables were found to be average speed, carriageway width and percentage of heavy vehicles. For single-carriageways, the different analysis developed did not reach a proper model for the explanation of White Road Sections. However, it can be assumed that the average values of the variables of traffic volume, radius, visibility, superelevation and slope show significant differences in White Road Sections if compared with others, which also vary with traffic volumes. Results obtained should be considered as a conclusion of a preliminary analysis, as there are other parameters, not only design-related, but also regarding traffic, environment, human factor and vehicle which could have an influence in the fact under research, but this information has not been considered in the analysis, as it was not available. In parallel, the analysis of the circumstances around the trip, including its typology and motivation is an interesting source of information, from which data are not available; the availability of this information would be useful for the improvement of accident analysis, in general, and for this research work, in particular. In addition, there are some limitations in the development of the research work; it would be necessary to develop an in-depth analysis in the future, thus assuming new research lines of interest.
Resumo:
This study focuses on the relationship between CO2 production and the ultimate hatchability of the incubation. A total amount of 43316 eggs of red-legged partridge (Alectoris rufa) were supervised during five actual incubations: three in 2012 and two in 2013. The CO2 concentration inside the incubator was monitored over a 20-day period, showing sigmoidal growth from ambient level (428 ppm) up to 1700 ppm in the incubation with the highest hatchability. Two sigmoid growth models (logistic and Gompertz) were used to describe the CO2 production by the eggs, with the result that the logistic model was a slightly better fit (r2=0.976 compared to r2=0.9746 for Gompertz). A coefficient of determination of 0.997 between the final CO2 estimation (ppm) using the logistic model and hatchability (%) was found.
Resumo:
Sob as condições presentes de competitividade global, rápido avanço tecnológico e escassez de recursos, a inovação tornou-se uma das abordagens estratégicas mais importantes que uma organização pode explorar. Nesse contexto, a capacidade de inovação da empresa enquanto capacidade de engajar-se na introdução de novos processos, produtos ou ideias na empresa, é reconhecida como uma das principais fontes de crescimento sustentável, efetividade e até mesmo sobrevivência para as organizações. No entanto, apenas algumas empresas compreenderam na prática o que é necessário para inovar com sucesso e a maioria enxerga a inovação como um grande desafio. A realidade não é diferente no caso das empresas brasileiras e em particular das Pequenas e Médias Empresas (PMEs). Estudos indicam que o grupo das PMEs particularmente demonstra em geral um déficit ainda maior na capacidade de inovação. Em resposta ao desafio de inovar, uma ampla literatura emergiu sobre vários aspectos da inovação. Porém, ainda considere-se que há poucos resultados conclusivos ou modelos compreensíveis na pesquisa sobre inovação haja vista a complexidade do tema que trata de um fenômeno multifacetado impulsionado por inúmeros fatores. Além disso, identifica-se um hiato entre o que é conhecido pela literatura geral sobre inovação e a literatura sobre inovação nas PMEs. Tendo em vista a relevância da capacidade de inovação e o lento avanço do seu entendimento no contexto das empresas de pequeno e médio porte cujas dificuldades para inovar ainda podem ser observadas, o presente estudo se propôs identificar os determinantes da capacidade de inovação das PMEs a fim de construir um modelo de alta capacidade de inovação para esse grupo de empresas. O objetivo estabelecido foi abordado por meio de método quantitativo o qual envolveu a aplicação da análise de regressão logística binária para analisar, sob a perspectiva das PMEs, os 15 determinantes da capacidade de inovação identificados na revisão da literatura. Para adotar a técnica de análise de regressão logística, foi realizada a transformação da variável dependente categórica em binária, sendo grupo 0 denominado capacidade de inovação sem destaque e grupo 1 definido como capacidade de inovação alta. Em seguida procedeu-se com a divisão da amostra total em duas subamostras sendo uma para análise contendo 60% das empresas e a outra para validação (holdout) com os 40% dos casos restantes. A adequação geral do modelo foi avaliada por meio das medidas pseudo R2 (McFadden), chi-quadrado (Hosmer e Lemeshow) e da taxa de sucesso (matriz de classificação). Feita essa avaliação e confirmada a adequação do fit geral do modelo, foram analisados os coeficientes das variáveis incluídas no modelo final quanto ao nível de significância, direção e magnitude. Por fim, prosseguiu-se com a validação do modelo logístico final por meio da análise da taxa de sucesso da amostra de validação. Por meio da técnica de análise de regressão logística, verificou-se que 4 variáveis apresentaram correlação positiva e significativa com a capacidade de inovação das PMEs e que, portanto diferenciam as empresas com capacidade de inovação alta das empresas com capacidade de inovação sem destaque. Com base nessa descoberta, foi criado o modelo final de alta capacidade de inovação para as PMEs composto pelos 4 determinantes: base de conhecimento externo (externo), capacidade de gestão de projetos (interno), base de conhecimento interno (interno) e estratégia (interno).
Resumo:
Despite the vast research examining the evolution of Caribbean education systems, little is chronologically tied to the postcolonial theoretical perspectives of specific island-state systems, such as the Jamaican education system and its relationship with the underground shadow education system. This dissertation study sought to address the gaps in the literature by critically positioning postcolonial theories in education to examine the macro- and micro-level impacts of extra lessons on secondary education in Jamaica. The following postcolonial theoretical (PCT) tenets in education were contextualized from a review of the literature: (a) PCT in education uses colonial discourse analysis to critically deconstruct and decolonize imperialistic and colonial representations of knowledge throughout history; (b) PCT in education uses an anti-colonial discursive framework to re-position indigenous knowledge in schools, colleges, and universities to challenge hegemonic knowledge; (c) PCT in education involves the "unlearning" of dominant, normative ideologies, the use of self-reflexivity, and deconstruction; and (d) PCT in education calls for critical pedagogical approaches that reject the banking concept of education and introduces inclusive pedagogy to facilitate "the passage from naïve to critical transitivity" (Freire, 1973, p. 32). Specifically, using a transformative mixed-methods design, grounded and informed by a postcolonial theoretical lens, I quantitatively uncovered and then qualitatively highlighted how if at all extra lessons can improve educational outcomes for students at the secondary level in Jamaica. Accordingly, the quantitative data was used to test the hypotheses that the practice of extra lessons in schools is related to student academic achievement and the practice of critical-inclusive pedagogy in extra lessons is related to academic achievement. The two-level hierarchical linear model analysis revealed that hours spent in extra lessons, average household monthly income, and critical-inclusive pedagogical tents were the best predictors for academic achievement. Alternatively, the holistic multi-case study explored how extra-lessons produces increased academic achievement. The data revealed new ways of knowledge construction and critical pedagogical approaches to galvanize systemic change in secondary education. Furthermore, the data showed that extra lessons can improve educational outcomes for students at the secondary level if the conditions for learning are met. This study sets the stage for new forms of knowledge construction and implications for policy change.