Search Results (8)

Categorical data analysis becomes challenging when high-dimensional sparse covariates are involved, which is often the case for omics data. We introduce a statistical procedure based on multinomial logistic regression analysis for such scenarios, including variable screening, model selection, order selection for response categories, and variable selection. We perform our procedure on high-dimensional gene expression data with 801 patients, 2426 genes, and five types of cancerous tumors. As a result, we recommend three finalized models: one with 74 genes achieves extremely low cross-entropy loss and zero predictive error rate based on a five-fold cross-validation; and two other models with 31 and 4 genes, respectively, are recommended for prognostic multi-gene signatures. Full article

Car ownership and use in the Kingdom of Saudi Arabia (KSA) are very high due to the high income, the low fuel prices and the near absence of public transportation in the Kingdom. Currently, the Kingdom is going through a massive transformation and entering a new era of national reforms. One of the main aims of the national reforms is to reduce car dependency and enhance more sustainable options of travel such as public transportation in the KSA. In order to achieve such an aim, there are two hurdles: Firstly, there must be a provision of decent public transportation options, and secondly, there is a need to influence travel behaviour and encourage the shift from private cars to public transportation. For example, in Riyadh city, an impressive metro system is being constructed and will start operation in 2023. To influence travel behaviour, travel demand management measures (TDM), in particular pricing measures, can be adopted and implemented, in order to help and support achieving the target. The main aim of this paper, therefore, is to assess the attitudes of Saudi nationals towards—and willingness to accept—pricing measures and their possible impacts on their travel behaviour in the city of Riyadh. The methodology includes collecting data using an online survey on travel behaviour and attitudes in Riyadh and calibrating multinomial logit modal choice models. The participants in the survey were asked to report their support of the pricing measures for the objective of reducing congestion in the city, improving road safety or reducing travel time. The results show the highest support towards pricing measures for improving road safety, reducing travel times and, lastly, reducing congestion in the city. Full article

Recent years have seen a considerable shift in the focus of public investment agencies from extensive roadway networks to a more planned approach that meets environmental, cost, and social dimensions more aptly. Past research has mainly explored the engineering aspect and cost parameters, while the human or social component is often neglected. This study aims to identify the trip-making behaviour of residents in an urban area towards bus transport network enhancement. Abu Dhabi, the location of study, is heavily dependent upon car travel, creating much congestion, which the local government seeks to address by enhanced public transport. This work examined eight public-transport routes in two zones, with data collected on both weekdays (n = 751) and weekends (n = 769). Multinomial logistic regression models showed that respondents highlighted overcrowded buses and traffic congestion as two of the main hurdles pertinent to urban routes in the bus network influencing their mode choice. Proposals pertinent to the local authority for further consideration need to factor in current low satisfaction with bus transit network coverage, low satisfaction with the quality of bus rides, inhibiting a mode shift from cars/taxis towards buses, cumulative income profiles of public-transport users, with findings that the low-income bracket is already at saturation, and that reducing congestion needs innovative (sociodynamic rather than technical road network) public-transport solutions. Full article

Mexico has the largest Indigenous population in the Americas and the most native languages in the region. These Indigenous peoples face a similar set of structural barriers to achieving more sustainable livelihoods, including criminal violence and huge hurdles to accumulating assets, in addition to their poverty. The purpose of this paper is to identify the main drivers of sustainable livelihood strategies in Indigenous households in rural Mexico. Using cluster analysis and a multinomial logit model based on a mixed approach that employs a traditional perspective of development alongside the sustainable livelihoods approach (SLA), our results suggest that a significant proportion of Indigenous households engage in livelihoods linked to the environment and nature, while only a small segment of households has been able to accumulate assets and adopt more profitable non-farming livelihoods. Our findings also reveal how the creation of human capital, the provision of basic services, and support to mitigate the effects of extreme weather all contribute to reducing risk for Indigenous households. The findings suggest that public policies must target these specific issues in order to solve structural problems that limit the efficacy with which Indigenous households use their family assets. Full article

(1) Background: Rift Valley fever (RVF) outbreaks in domestic ruminants have severe socio-economic impacts. Climate-based continental predictions providing early warnings to regions at risk for RVF outbreaks are not of a high enough resolution for ruminant owners to assess their individual risk. (2) Methods: We analyzed risk factors for RVF occurrence and severity at the farm level using the number of domestic ruminant deaths and abortions reported by farmers in central South Africa during the 2010 RVF outbreaks using a Bayesian multinomial hurdle framework. (3) Results: We found strong support that the proportion of days with precipitation, the number of water sources, and the proportion of goats in the herd were positively associated with increased severity of RVF (the numbers of deaths and abortions). We did not find an association between any risk factors and whether RVF was reported on farms. (4) Conclusions: At the farm level we identified risk factors of RVF severity; however, there was little support for risk factors of RVF occurrence. The identification of farm-level risk factors for Rift Valley fever virus (RVFV) occurrence would support and potentially improve current prediction methods and would provide animal owners with critical information needed in order to assess their herd’s risk of RVFV infection. Full article

Institutional and policy-induced factors affect farmers’ decisions on the choice of the market to sell their staple foods. This results in low motivation to participate in the production and agricultural commodities’ commercialization. This study determines specific institutional and policy-induced factors affecting the farmers’ decisions regarding the staple food market choice in Tanzania. The study uses household survey data collected from 820 farmers raising staple food crops (maize, rice, sorghum, and millet) randomly selected from the Dodoma and Morogoro regions, Tanzania. The index method, descriptive statistics, and choice model (multinomial logit model) are used for data analysis. Qualitative policy analysis is used for analyzing policy-induced factors. Findings show a low level of integration of farmers into staple food markets, with female-headed households facing more hurdles in accessing markets than male-headed households. Age, formal training, the value of agricultural production, membership in organizations, access to credit, contractual arrangements, and distance to markets are significant factors driving farmers to choose a particular market to sell their produces. Restriction of selling and use of staple food commodities, instability of food policy administration, and procedural operation obstacles are found to be key policy-induced factors affecting the marketing of staple food commodities in Tanzania. The scale of production, as depicted by the value of production, and supply contract arrangement with buyers are important factors to ensure that farming households excel in lucrative markets through increased economies of scale and the ability to reach critical volumes for supplying to various markets. Supporting market linkage and infrastructure, as well as enforcing transparent and non-restrictive food marketing policies, would help many farmers enter into contractual arrangements that increase market access and improve market choices. Full article

Breast cancer is the most prevalent female cancer in the US. Incidence rates are similar for white and black women but mortality rates are higher for black women. This study draws on rich, nationally representative data, the 2008–2015 Medical Expenditure Panel Surveys, to estimate effects of the Affordable Care Act (ACA) on reducing disparities in and access to use of diagnostic and medical services for black and Hispanic breast cancer survivors. Random effects multinomial logit, flexible hurdle and Box-Cox estimation techniques are used. The robust estimates indicate that the ACA narrowed the racial/ethnic disparity in health insurance coverage, health care utilization and out-of-pocket prescription drug expenditures among breast cancer survivors. Gaps in uninsurance significantly declined for black and Hispanic survivors. Hispanic women generally and black breast cancer survivors specifically increased use of mammography services post-ACA. The ACA did not significantly impact disparities in physician utilization or out-of-pocket prescription drug expenditures for Hispanic survivors, while there were substantive improvements for black breast cancer survivors. The paper concludes with a discussion of the strengths and limitations of the ACA for reducing disparities and improving health outcomes for a growing population of breast cancer survivors in the US. Full article

We explore the extent to which claim incidence in Disability Income Insurance (DII) is affected by changes in the unemployment rate in Australia. Using data from 1986 to 2001, we fit a hurdle model to explore the presence and magnitude of the effect of changes in unemployment rate on the incidence of DII claims, controlling for policy holder characteristics and seasonality. We find a clear positive association between unemployment and claim incidence, and we explore this further by gender, age, deferment period, and occupation. A multinomial logistic regression model is fitted to cause of claim data in order to explore the relationship further, and it is shown that the proportion of claims due to accident increases markedly with rising unemployment. The results suggest that during periods of rising unemployment, insurers may face increased claims from policy holders with shorter deferment periods for white-collar workers and for medium and heavy manual workers. Our findings indicate that moral hazard may have a material impact on DII claim incidence and insurer business in periods of declining economic conditions. Full article