Many studies have shown that intersections are among the most dangerous locations of a roadway network. Therefore, there is a need to understand the factors that contribute to traffic crashes at such locations. One approach is to model crash occurrences based on configuration, geometric characteristics and traffic. Instead of combining all variables and crash types to create a single statistical model, this analysis created several models that address the different factors that affect crashes, by type of collision as well as injury level, at signalized intersections. The first objective was to determine if there is a difference between important variables for models based on individual crash types or severity levels and aggregated models. The second objective of this research was to investigate the quality and completeness of the crash data and the effect that incomplete data has on the final results. A detailed and thorough data collection effort was necessary for this research to ensure the quality and completeness of this data. Multiple agencies were contacted and databases were crosschecked (i.e. state and local jurisdictions/agencies). Information (including geometry, configuration and traffic characteristics) was collected for a total of 832 intersections and over 33,500 crashes from Brevard, Hillsborough and Seminole Counties and the City of Orlando. Due to the abundance of data collected, a portion was used as a validation set for the tree-based regression. Hierarchical tree-based regression (HTBR) and ordered probit models were used in the analyses. HTBR was used to create models for the expected number of crashes for collision type as well as injury level. Ordered probit models were only used to predict crash severity levels due to the ordinal nature of this dependent variable. Finally, both types of models were used to predict the expected number of crashes. More specifically, tree-based regression was used to consider the difference in the relative importance of each variable between the different types of collisions. First, regressions were only based on crashes available from state agencies to make the results more comparable to other studies. The main finding was that the models created for angle and left turn crashes change the most compared to the model created from the total number of crashes reported on long forms (restricted data usually available at state agencies). This result shows that aggregating the different crash types by only estimating models based on the total number of crashes will not predict the number of expected crashes as accurately as models based on each type of crash separately. Then, complete datasets (full dataset based on crash reports collected from multiple sources) were used to calibrate the models. There was consistently a difference between models based on the restricted and complete datasets. The results in this section show that it is important to include minor crashes (usually reported on short forms and ignored) in the dataset when modeling the number of angle or head-on crashes and less important to include minor crashes when modeling rear-end, right turn or sideswipe crashes. This research presents in detail the significant geometric and traffic characteristics that affect each type of collision. Ordered probit models were used to estimate crash injury severity levels for three different types of models; the first one based on collision type, the second one based on intersection characteristics and the last one based on a significant combination of factors in both models. Both the restricted and complete datasets were used to create the first two model types and the output was compared. It was determined that the models based on the complete dataset were more accurate. However, when compared to the tree-based regression results, the ordered probit model did not predict as well for the restricted dataset based on intersection characteristics. The final ordered probit model showed that crashes involving a pedestrian/bicyclist have the highest probability of a severe injury. For motor vehicle crashes, left turn, angle, head-on and rear-end crashes cause higher injury severity levels. Division (a median) on the minor road, as well as a higher speed limit on the minor road, was found to lower the expected injury level. This research has shed light on several important topics in crash modeling. First of all, this research demonstrated that variables found to be significant in aggregated crash models may not be the same as the significant variables found in models based on specific crash types. Furthermore, variables found to be significant in crash type models typically changed when minor crashes were added to complete the dataset. Thirdly, ordered probit models based on significant crash-type and intersection characteristic variables have greater crash severity prediction power, especially when based on the complete dataset. Lastly, upon comparison between tree-based regression and ordered probit models, it was found that the tree-based regression models better predicted the crash severity levels.

The situation that China's pensions cannot cover the expenditure is becoming more and more serious. On the one hand, it is to increase the rate of return of enterprise annuities. On the other hand, it is to increase the participation rate of enterprise annuities. In order to improve the participation rate of enterprise annuity, it is of great significance to solve the problem of insufficient funds of enterprise annuity from the aspect of supply. Based on this, this dissertation conducts detailed research, focusing on the impact of relevant factors on the participation rate of enterprise annuity from the enterprise level and the individual level. After making a detailed overview of the situation of domestic enterprise annuity, this dissertation analyzes the influencing factors of the participation rate of enterprise annuity of China based on the latest nationally representative micro data CHIP 2018. The analysis uses the "bivariate Probit model", that is, the enterprise level and the individual level, employing 0-1 bivariate as the dependent variables and employee income, employee education, employee gender, enterprise income as independent variables. The analysis also includes other control variables. The empirical evidence found that employee income, employee education, and employee gender have impacts on employee participation in enterprise annuity; enterprise ownership, company income, and the industry in which the company is located have impacts on whether the enterprise establishes an enterprise annuity plan. In addition, there are differences in the state-owned system and private system and industry differences on the establishment of enterprise annuity plans. Finally, this dissertation gives relevant policy suggestions that may provide some theoretical guidance for increasing the participation rate of enterprise annuity.Key words: Enterprise annuity; Participation rate; Bivariate Probit model; Policy suggestions. / Business Administration/Interdisciplinary

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Sigmoid curves have found broad applicability in biological sciences and biopharmaceutical research during the last decades. A well planned experiment design is essential to accurately estimate the parameters of the model. In contrast to a large literature and extensive results on optimal designs for linear models, research on the design for nonlinear, including sigmoid curve, models has not kept pace. Furthermore, most of the work in the optimal design literature for nonlinear models concerns the characterization of minimally supported designs. These minimal, optimal designs are frequently criticized for their inability to check goodness of fit, as there are no additional degrees of freedom for the testing. This design issue can be a serious problem, since checking the model adequacy is of particular importance when the model is selected without complete certainty. To assess for lack of fit, we must add at least one extra distinct design point to the experiment. The goal of this dissertation is to identify optimal or highly efficient designs capable of checking the fit for sigmoid curve models. In this dissertation, we consider some commonly used sigmoid curves, including logistic, probit and Gompertz models with two, three, or four parameters. We use D-optimality as our design criterion. We first consider adding one extra point to the design, and consider five alternative designs and discuss their suitability to test for lack of fit. Then we extend the results to include one more additional point to better understand the compromise among the need of detecting lack of fit, maintaining high efficiency and the practical convenience for the practitioners. We then focus on the two-parameter Gompertz model, which is widely used in fitting growth curves yet less studied in literature, and explore three-point designs for testing lack of fit under various error variance structures. One reason that nonlinear design problems are so challenging is that, with nonlinear models, information matrices and optimal designs depend on the unknown model parameters. We propose a strategy to bypass the obstacle of parameter dependence for the theoretical derivation. This dissertation also successfully characterizes many commonly studied sigmoid curves in a generalized way by imposing unified parameterization conditions, which can be generalized and applied in the studies of other sigmoid curves. We also discuss Gompertz model with different error structures in finding an extra point for testing lack of fit. / Statistics

Since the federal budget for EFNEP is over $66 million, it is crucial to know the effectiveness of program attributes that may bolster its effectiveness. The aim of this study was to determine how effectiveness of Youth EFNEP programs in Virginia is affected by participant, instructional and curriculum attributes for youth enrolled in Healthy Weight for Healthy Kids (HWHK). An ordered probit model was employed to study how these attributes affect dependent variables: Whole Grain, Fruits, Colored Vegetables, MyPlate, and Breathe Hard behavioral scores. The model assessed the probability of a participant having an improved score or improved behavior. Participant Attributes Results: In general, the chosen variables for participant characteristics consistently reduced the probability of participants having an improved behavior score. Instructional Attributes Results: African Americans Program Assistants were consistently associated with negative marginal effects on positive behavioral scores with the exception of the positive Breathe Hard behavioral score. Other PA attributes were not consistently associated with any behavioral models but were heterogeneous in terms of their marginal effects on the positive behavioral scores. Curriculum Attributes results: The curriculum attributes had more positive marginal effects than negative marginal effects across all the five behavioral scores. Attributes that were consistently associated with having a positive marginal effect on behavioral scores were program duration, smart foods lesson, and lesson duration. Other HWHK lessons were not consistent in increasing or reducing the probability of an improved behavior. / Master of Science

Smallholder households in Haiti face many natural resource management challenges. Agricultural production occurs on deforested hillsides prone to erosion. Charcoal is in an important source of income, and woodfuel stocks are often over-exploited. Donor-funded projects and non- governmental organizations have made large investments in programs that promote soil conservation practices and reforestation. Despite the magnitude of the problems and the amount invested, there are relatively few economic analyses of the long-term adoption of soil conservation practices and woodfuel management. This dissertation uses an economics approach to examine the adoption of conservation practices and the management of woodfuel resources in Central Haiti using cross-sectional data covering 600 households. The results show that plot and household characteristics have different effects on adoption across different classes of soil practices, particularly with regard to perceived soil quality, market access, and household health status. The results also provide evidence of the management of charcoal woodfuel stocks on private land. These findings inform the design and targeting of new programs related to soil conservation and reforestation in Haiti and other developing countries. / Ph. D.

The caseloads of food stamp program and welfare program experienced sharp drops among non-metropolitan single female-headed families with children (SFHFwC) after welfare reform in 1996. There is concern that leaving welfare program has led to nonparticipation in food stamp program due to multiple reasons. This study conducts an empirical analysis of non-metropolitan SFHFwC's participation in food stamp program and welfare program, using the 1993 and 1999 CPS data. Results from using reduced-form probit model, bivariate probit model and structural probit model are compared. The reduced-form probit model considers participation in both programs as functions of all exogenous variables. The bivariate probit model allows correlation between the participation in the two programs. The structural probit model considers participation in welfare as an endogenous variable of FSP participation. Empirical analysis is also conducted through the comparison across years and between southern and the remaining U.S. states. We found that welfare participation has a significant and positive impact on FSP participation. Households leaving welfare are more likely not to participate in FSP. Further, welfare participation is more important in determining FSP participation in 1999 than in 1993. Residence in South has a significant and negative impact in welfare participation in 1999, but has no significant impact on FSP participation in either year. Incomes and number of young children are the other major determinants of participation in both programs. Policy suggestions include improving economic situation to reduce FSP caseloads on one side, and providing more information about FSP eligibility to welfare leavers to ensure their food safety on the other side. / Master of Science

Made available in DSpace on 2016-04-26T20:48:46Z (GMT). No. of bitstreams: 1 Dissertacao Adriana Keiko Miyake.pdf: 3746552 bytes, checksum: 6dd1aaa0e7aa880c56b3871870d50940 (MD5) Previous issue date: 2006-06-20 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / As transformações ocorridas nas últimas décadas na economia internacional provocaram graves crises monetárias e fmanceiras em diversos países, resultando em crises cambiais e no abandono do regime de câmbio fixo. O aumento do poder do capital financeiro sobre o produtivo, decorrente da maior abertura e da desregulamentação dos mercados financeiros, foi um dos fatores que aumentou a vulnerabilidade de economias menos preparadas para essas mudanças, como foi o caso de muitos países em desenvolvimento. Ainda, a abertura comercial ocorrida nesses países expôs seu setor produtivo à crescente concorrência externa de grandes empresas multinacionais. Aliada a esses fatores, a forma com que a política foi conduzida por seus respectivos governos contribuiu para a deflagração da cnse. A crise cambial brasileira, ocorrida no início de 1999, acarretou problemas para toda a economia brasileira. Diante disso, este trabalho procurou estudar os fatores que poderiam ser apontados como responsáveis por esse acontecimento, para que, no futuro, situações semelhantes sejam previstas com maior antecedência e para que medidas sejam tomadas para evitar este tipo de desfecho. Foi feito um acompanhamento da economia, ao longo da década de 1990, para se identificar as variáveis que levaram à crise cambial. A partir disso, foi utilizado um instrumental matemático (regressão do tipo Probit) para se chegar a um modelo econométrico que relacionasse essas variáveis à probabilidade de ocorrência de crise. Diferentemente do que ocorreu nos países do leste asiático, que suscitou o desenvolvimento dos modelos chamados de terceira geração, o resultado obtido no caso brasileiro se mostrou em conformidade com aspectos tanto dos modelos de primeira quanto de segunda geração