Compare the accuracy of two continuous-scale tests is increasing important when a new test is developed. The traditional approach that compares the entire areas under two Receiver Operating Characteristic (ROC) curves is not sensitive when two ROC curves cross each other. A better approach to compare the accuracy of two diagnostic tests is to compare the areas under two ROC curves (AUCs) in the interested specificity interval. In this thesis, we have proposed bootstrap and empirical likelihood (EL) approach for inference of the difference between two partial AUCs. The empirical likelihood ratio for the difference between two partial AUCs is defined and its limiting distribution is shown to be a scaled chi-square distribution. The EL based confidence intervals for the difference between two partial AUCs are obtained. Additionally we have conducted simulation studies to compare four proposed EL and bootstrap based intervals.

It is an important step in clinical practice to discriminate real diseased patients from healthy persons. It would be great to get such discrimination from some common information like personal information, life style, and the contact with diseased patient. In this study, a score is calculated for each patient based on a survey through generalized linear model, and then the diseased status is decided according to previous sexually transmitted diseases (STDs) records. This study will facilitate clinics in grouping patients into real diseased or healthy, which in turn will affect the method clinics take to screen patients: complete screening for possible diseased patient and some common screening for potentially healthy persons.

Credit Line Analysis plays a very important role in the housing market, especially with the situation of large number of frozen loans during the current financial crisis. In this thesis, we apply the methods of kernel estimate and the Receiver Operating Characteristic (ROC) curve in the credit loan application process in order to help banks select the optimal threshold to differentiate good customers from bad customers. Better choice of the threshold is essential for banks to prevent loss and maximize profit from loans. One of the main advantages of our study is that the method does not require us to specify the distribution of the latent risk score. We apply bootstrap method to construct the confidence interval for the estimate.

Receiver Operating Characteristic (ROC) curves are often used to evaluate the prognostic performance of a continuous biomarker. In a previous research, a non-parametric ROC approach was introduced to compare two biomarkers with repeated measurements. An asymptotically normal statistic, which contains the subject-specific weights, was developed to estimate the areas under the ROC curve of biomarkers. Although two weighting schemes were suggested to be optimal when the within subject correlation is 1 or 0 by the previous study, the universal optimal weight was not determined. We modify this asymptotical statistic to compare AUCs between two correlated groups and propose a solution to weight optimization in non-parametric AUCs comparison to improve the efficiency of the estimator. It is demonstrated how the Lagrange multiplier can be used as a strategy for finding the weights which minimize the variance function subject to constraints. We show substantial gains of efficiency by using the novel weighting scheme when the correlation within group is high, the correlation between groups is high, and/or the disease incidence is small, which is the case for many longitudinal matched case-control studies. An illustrative example is presented to apply the proposed methodology to a thyroid function dataset. Simulation results suggest that the optimal weight performs well with a sample size as small as 50 per group.

BACKGROUND: Type 2 diabetes and cardiovascular disease (CVD) are among the leading causes of death in the United States. The Metabolic Syndrome, which comprises a cluster of cardiometabolic risk factors, puts individuals at increased risk for these diseases. It is therefore important that people with Metabolic Syndrome, at high risk for CVD and type 2 diabetes, are identified and treated. Since it may not often be practical to obtain the laboratory measures necessary for diagnosing the Metabolic Syndrome, simple anthropometric measures are a useful way of quickly identifying individuals at increased risk for the Metabolic Syndrome. OBJECTIVE: The purpose of this thesis is to evaluate the utility of three of the most commonly used anthropometric measures – Body Mass Index (BMI), Waist Circumference (WC), and Waist-to-Height Ratio (WC) – for classifying individuals with and without the Metabolic Syndrome and its component risk factors in the United States. Using Receiver Operating Characteristic (ROC) curve analysis and Area Under the Curve (AUC) statistics, this thesis will assess the utility of each body measurement and compare it to BMI. METHODS: A large, multi-ethnic, nationally representative sample from the National Health and Nutrition Examination Survey (NHANES) 2007-2010 was used for this analysis. The study sample was restricted to adults aged 20-65 with complete information on height, weight, waist circumference, blood pressure, HDL cholesterol, fasting glucose, and triglycerides (n=3,769). In order to compare the utility of different anthropometric measures for classification, weighted ROC curves were constructed for each anthropometric measure-outcome combination and AUC statistics were compared. AUC statistics were calculated by approximating the definite integral of the ROC curves with the trapezoidal rule. Variances for AUC statistics and differences in AUC statistics were estimated with jackknife repeated replication. Analyses were completed for the entire sample and separately for non-Hispanic whites, non-Hispanic blacks, and Mexican Americans. RESULTS: For the entire sample, WC (AUC=0.752) did a better job than BMI (AUC=0.728) at classifying individuals with and without the Metabolic Syndrome (p CONCLUSION: Waist circumference should be considered, especially over BMI, for risk stratification in clinical settings and research. Further research should attempt to identify optimum waist circumference cut points for use in the US population.

Emergency department (ED) overcrowding is a challenge faced by many hospitals. One approach to mitigate overcrowding is to anticipate high levels of overcrowding. The purpose of this study was to forecast a measure of ED overcrowding four hours in advance to allow clinicians to prepare for high levels of overcrowding. The chosen measure of ED overcrowding was ED length of stay compliance measures set by the Ontario government. A feed-forward artificial neural network (ANN) was designed to perform a time series forecast on the number of patients that were non-compliant. Using the ANN compared to historical averages, a 70% reduction in the root mean squared error was observed as well as good discriminatory ability of the ANN model with an area under the receiver operating characteristic curve of 0.804. Therefore, using ANNs to forecast ED overcrowding gives clinicians an opportunity to be proactive, rather than reactive, in ED overcrowding crises.

Emergency department (ED) overcrowding is a challenge faced by many hospitals. One approach to mitigate overcrowding is to anticipate high levels of overcrowding. The purpose of this study was to forecast a measure of ED overcrowding four hours in advance to allow clinicians to prepare for high levels of overcrowding. The chosen measure of ED overcrowding was ED length of stay compliance measures set by the Ontario government. A feed-forward artificial neural network (ANN) was designed to perform a time series forecast on the number of patients that were non-compliant. Using the ANN compared to historical averages, a 70% reduction in the root mean squared error was observed as well as good discriminatory ability of the ANN model with an area under the receiver operating characteristic curve of 0.804. Therefore, using ANNs to forecast ED overcrowding gives clinicians an opportunity to be proactive, rather than reactive, in ED overcrowding crises.

The collection of crop yield data has become much easier with the introduction of technologies such as the Global Positioning System (GPS), ground-based yield sensors, and Geographic Information Systems (GIS). This explosive growth and widespread use of spatial data has challenged the ability to derive useful spatial knowledge. In addition, outlier detection as one important pre-processing step remains a challenge because the technique and the definition of spatial neighbourhood remain non-trivial, and the quantitative assessments of false positives, false negatives, and the concept of region outlier remain unexplored. The overall aim of this study is to evaluate different spatial outlier detection techniques in terms of their accuracy and computational efficiency, and examine the performance of these outlier removal techniques in a site-specific management context. In a simulation study, unconditional sequential Gaussian simulation is performed to generate crop yield as the response variable along with two explanatory variables. Point and region spatial outliers are added to the simulated datasets by randomly selecting observations and adding or subtracting a Gaussian error term. With simulated data which contains known spatial outliers in advance, the assessment of spatial outlier techniques can be conducted as a binary classification exercise, treating each spatial outlier detection technique as a classifier. Algorithm performance is evaluated with the area and partial area under the ROC curve up to different true positive and false positive rates. Outlier effects in on-farm research are assessed in terms of the influence of each spatial outlier technique on coefficient estimates from a spatial regression model that accounts for autocorrelation. Results indicate that for point outliers, spatial outlier techniques that account for spatial autocorrelation tend to be better than standard spatial outlier techniques in terms of higher sensitivity, lower false positive detection rate, and consistency in performance. They are also more resistant to changes in the neighbourhood definition. In terms of region outliers, standard techniques tend to be better than spatial autocorrelation techniques in all performance aspects because they are less affected by masking and swamping effects. In particular, one spatial autocorrelation technique, Averaged Difference, is superior to all other techniques in terms of both point and region outlier scenario because of its ability to incorporate spatial autocorrelation while at the same time, revealing the variation between nearest neighbours. In terms of decision-making, all algorithms led to slightly different coefficient estimates, and therefore, may result in distinct decisions for site-specific management. The results outlined here will allow an improved removal of crop yield data points that are potentially problematic. What has been determined here is the recommendation of using Averaged Difference algorithm for cleaning spatial outliers in yield dataset. Identifying the optimal nearest neighbour parameter for the neighbourhood aggregation function is still non-trivial. The recommendation is to specify a large number of nearest neighbours, large enough to capture the region size. Lastly, the unbiased coefficient estimates obtained with Average Difference suggest it is the better method for pre-processing spatial outliers in crop yield data, which underlines its suitability for detecting spatial outlier in the context of on-farm research.

No description available.

A dor lombar (DL) é uma das principais causas de incapacidade e de ônus econômico para as comunidades, sendo que, sua presença na infância e adolescência está associada à ocorrência na vida adulta. Similarmente, a alteração do equilíbrio sagital pélvico (ESP), considerada um importante fator de risco no desenvolvimento de alterações posturais e de síndromes dolorosas, tende a se manter também durante a adultez. Assim, verificar a ocorrência destes problemas, bem como identificar os fatores associados a estes durante a infância e adolescência pode auxiliar na elaboração de estratégias preventivas. Este estudo tem como objetivos: 1) Identificar a capacidade, dos pontos de corte disponíveis na literatura para as variáveis da aptidão física relacionada à saúde (ApFRS), de triagem de escolares com maior probabilidade de apresentarem DL e/ou alteração no ESP e propor novos pontos de corte, para crianças e jovens brasileiros, para força/resistência abdominal e flexibilidade; 2) Descrever a ocorrência de DL e verificar seus fatores associados; 3) Descrever a ocorrência de alteração no ESP e verificar seus fatores associados. A amostra foi composta por 787 crianças e adolescentes selecionados por conveniência. A DL foi avaliada através de questionário e o ESP foi verificado através do alinhamento entre a espinha ilíaca anterossuperior e a espinha ilíaca posteroinferior. Foi medida a flexibilidade (sentar e alcançar com e sem banco), a força/resistência abdominal (abdominais em um minuto), a mobilidade lombar (Schober modificado), a ativação do músculo transverso do abdome (Stabilizer), a circunferência do abdome, o peso, a estatura e calculado o índice de massa corporal (IMC). Através da curva Receiver Operating Characteristics (ROC) entre as variáveis da ApFRS e DL e/ou alteração do ESP (desfecho) foram identificados os valores dos pontos de corte que apresentaram melhor ajustamento entre sensibilidade e especificidade. Tabelas de contingência foram utilizadas (entre os pontos de corte disponíveis na literatura, além dos propostos pelo presente estudo, e o desfecho) para calcular a sensibilidade e a especificidade. Para verificar a associação das variáveis independentes ao desfecho, foi estimada a razão de prevalência (RP) através da Regressão de Poisson. Por fim, elaboramos um modelo múltiplo para a DL e outro para a alteração do ESP. Os resultados demonstraram que os PC disponíveis na literatura não apresentaram bom ajuste entre sensibilidade e especificidade. Dentre as propostas analisadas, a do presente estudo foi a que apresentou melhor capacidade de triagem de escolares com risco aumentado à ocorrência de DL e/ou alteração do ESP. A ocorrência de DL na amostra estudada foi de 31,6% e os fatores associados foram a idade, para os dois sexos, adicionado da flexibilidade, para os meninos, e da interação entre flexibilidade e força/resistência abdominal, para as meninas. A ocorrência de alteração do ESP esteve presente em 60,2% dos escolares. As variáveis que compuseram o modelo ajustado foram a idade, a ativação do músculo transverso do abdome, o IMC, a flexibilidade e a mobilidade lombar. Encontramos elevados percentuais de DL e de alteração do ESP em crianças e adolescentes e verificamos que níveis adequados de ApFRS estão associados à diminuição na probabilidade dessas ocorrências. Assim, sugerimos que os pontos de corte estabelecidos por este estudo sejam empregados na avaliação de escolares e que as variáveis da ApFRS sejam desenvolvidas nas aulas de educação física. / Low back pain (LBP) is a leading cause of disability and economical burden for communities. LBP in children and adolescents is associated to its occurrence in adulthood. Similarly, alteration in pelvic sagittal alignment (PSA) is considered as a risk factor to the development of postural abnormalities and pain syndromes. Also, its early occurrence trends to remain in adulthood. The aims of this study were 1) to verify the screening ability cutoff available in the literature for physical fitness variables (flexibility and abdominal strength) in identify schoolchildren with more probability of musculoskeletal problems (LBP and PSA alteration) and to propose new cutoffs; 2) To describe LBP occurrence and to identify its associated factors; 3) To describe the occurrence of PAS alteration and to identify its associated factors. The sample comprised 787 children and adolescents aged 7 to 17 selected by convenience. LBP was assessed by a questionnaire. PAS was verified by alignment between anterior superior iliac spine and posterior inferior iliac spine. Flexibility (sit and reach test with and without the bench), abdominal strength (sit ups test), lumbar mobility (modified Schober test), activation of transversus abdominis (stabilizer), abdominal circumference, height, weight and body mass index (BMI) were measured. By the Receiver Operating Characteristics (ROC) curve between physical fitness variables and outcome (LBP and/or PSA alteration) were identified the cutoff values that indicate the best balance between sensitivity and specificity. Contingency tables with physical fitness variables and outcome were used to calculate the sensibility and specificity of the cutoff available in literature and those proposed by the present study. Poisson regression was used to verify the association between exposure and outcome. A multivariable model was designed to LBP and another to PSA alteration. Results suggest that cutoff available in the literature has not a good fit between sensibility and specificity. The cutoff proposed by the present study was the one that showed the best screening ability of schoolchildren at increased LBP and/or PSA alteration risk. LBP occurrence was 31,6% and the associated factors were age, for both genders, plus flexibility, for boys, and interaction between flexibility and abdominal strength, for girls. The occurrence of the alteration of PSA was 60,2% and it was associated to age, activation of transversus abdominis, BMI, flexibility and lumbar mobility. We found high LBP and PSA alteration occurrence in schoolchildren. Adequate levels of physical fitness are associated with a lower probability of these occurrences. So, we suggest that the cutoffs found in this study are used in the evaluation of schoolchildren and that physical fitness variables are practiced at physical education classes.