Colorectal polyp prevention trials (PPTs) are randomized, placebo-controlled clinical trials that evaluate some chemo-preventive agent and include participants who will be followed for at least 3 years to compare the recurrence rates (counts) of adenomas. A large proportion of zero counts will likely be observed in both groups at the end of the observation period. Poisson general linear models (GLMs) are usually employed for estimation of recurrence in PPTs. Other models, including the negative binomial (NB2), zero-inflated Poisson (ZIP), and zero-inflated negative binomial (ZINB) may be better suited to handle zero-inflation or other forms of overdispersion that are common in count data. A model selection paradigm that determines a statistical approach for choosing the best fitting model for recurrence data is described. An example using a subset from a large Phase III clinical trial indicated that the ZINB model was the best fitting model for the data.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-05-11T18:00:44Z No. of bitstreams: 1 raquelcoelhoreis.pdf: 1431099 bytes, checksum: ddaa9cad218cf8c07ed0fb203e770ac4 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-05-17T15:21:45Z (GMT) No. of bitstreams: 1 raquelcoelhoreis.pdf: 1431099 bytes, checksum: ddaa9cad218cf8c07ed0fb203e770ac4 (MD5) / Made available in DSpace on 2017-05-17T15:21:45Z (GMT). No. of bitstreams: 1 raquelcoelhoreis.pdf: 1431099 bytes, checksum: ddaa9cad218cf8c07ed0fb203e770ac4 (MD5) Previous issue date: 2017-02-20 / O estudo tem como objetivo investigar os determinantes regionais e estruturais da ocorrência de ligações entre regiões nas redes sociais de colaborações no Brasil. Para isto, utiliza-se de dados de copatenteamento das produções tecnológicas, realizadas tanto por inventores brasileiros como destes em parceria com estrangeiros. Como possíveis determinantes das ligações nas redes de copatenteamento regional consideram-se tanto os aspectos econômicos, tecnológicos e de densidade demográfica das regiões quanto as próprias estruturas de topologia dos nós nas redes. Os dados para a pesquisa são fornecidos pelo Instituto Nacional de Propriedade Industrial (INPI), Relação Anual de Informações Sociais (RAIS), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) e Instituto Brasileiro de Geografia e Estatística (IBGE). Sendo assim, foi possível a construção de uma base de dados longitudinal para o período de 2001-2011 com abrangência geográfica mais desagregada de REGIC imediata, e investigação por meio de técnicas econométricas de dados em painel. A fim de atingir o objetivo proposto identificam-se duas redes no Brasil: rede inter-regional e internacional. Portanto, para ambas as redes aplicam-se duas abordagens. Primeiramente, utiliza-se um modelo voltado para dados truncados, Tobit, cuja variável dependente é dada pela razão entre o número de ligações e o total de patentes geradas pela região. E posteriormente, aplica-se um modelo para dados de contagem, Binomial Negativo Inflado em Zeros (ZINB), que considera o número absoluto de ligações de cada região nas redes. Como principais resultados evidencia-se que as ligações dos nós (regiões) são mais impactadas por aspectos da infraestrutura local, como nível de P&D, e por sua estrutura de posição na rede. No entanto, outras características locais e estruturais também merecem ser destacadas como a participação econômica das regiões, assim como os níveis de participação da indústria. / The study aims to investigate the regional and structural determinants of the links among regions in social networks of collaboration in Brazil. For this, we use patent database that possess information on Brazilian inventors’ residence address and on the nationality of all inventors responsible for the patent application in Brazilian Patent Office. We investigate which are the main regional determinants of the links in the Brazilian co-patenting networks taking into account variables that capture economic, technological and demographic density aspects of Brazilian regions, as well as the topology structures of the nodes in the networks. The database is provided by the National Institute of Industrial Property (INPI), the Annual Social Information Relation (RAIS), the Coordination for the Improvement of Higher Education Personnel (CAPES) and the Brazilian Institute of Geography and Statistics (IBGE). We consider a longitudinal database for the period 2001-2011 and apply panel data techniques in spatial unit of analysis corresponding to the Intermediate Areas of Urban Connectivity, according to the concept of Regions of Influence of Brazilian Cities (REGICs). Two types of networks are considered in Brazil: the inter-regional and the international ones. Therefore, for both types of networks two approaches are applied: 1) a truncated data model is used, i.e. Tobit, whose dependent variable is given by the ratio of the number of links to the number of patents generated by the region; and 2) a Zero-inflated negative binomial (ZINB) model is used, which considers the absolute number of inter-regional links among inventors in a certain region. The main results show that node (region) connections are more affected by aspects of local infrastructure, such as R&D level, and their position in the network. However, other local and structural characteristics also deserve to be highlighted as the economic participation of regions, as well as levels of capital goods imports and industry participation.

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Thesis (M.Sc. (Statistics)) -- University of Limpopo, 2020 / Background: Death and economic losses due to road traffic accidents (RTA) are huge global public health and developmental problems and need urgent attention. Each year nearly 1.24 million people die and millions suffer various forms of disability as a result of road accidents. This puts road traffic injuries (RTIs) as the eighth leading cause of death globally and RTIs are set to become the fifth leading cause of death worldwide by the year 2030 unless urgent actions are taken. Aim: In this paper, we investigate factors that contribute to road traffic deaths (RTDs) in the Limpopo province of South Africa using models such as the generalized linear models (GLM) and zero inflated models. Methods: The study was based on retrospective data that comprised of reports of 18,029 road traffic accidents and 4,944 road traffic deaths over the years 2009 – 2015. Generalized linear modelling and zero-inflated models were used to identify factors and determine their relationships to RTDs. Results: The data was split into two categories: deaths that occurred during holidays and those that occurred during non-holiday periods. It was found that the following variables, namely, Monday, human actions, vehicle conditions and vehicle makes, were significant predictors of RTDs during holidays. On the other hand, during non-holiday periods, weekend, Tuesday, Wednesday, national road, provincial road, sedan, LDV, combi and bus were found to be significant predictors of road traffic deaths. Conclusion: GLM techniques, such as the standard Poisson regression model and the negative binomial (NB) model, did little to explain the zero excess, therefore, zero-inflated models, such as zero-inflated negative binomial (ZINB), were found to be useful in explaining excess zeros. Recommendation: The study recommends that the government should make more human power available during the festive seasons, such as the December holidays, and over weekends.