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We consider the newly developed multinomial mixed-link models for a high-risk intestinal metaplasia (IM) study with DNA methylation data. Different from the traditional multinomial logistic models commonly used for categorical responses, the mixed-link models allow us to select the most appropriate link function for each category. We show that the selected multinomial mixed-link model (Model 1) using the total number of stem cell divisions (TNSC) based on DNA methylation data outperforms the traditional logistic models in terms of cross-entropy loss from ten-fold cross-validations with significant p-values 8.12 × 10 − 4 and 6.94 × 10 − 5 . Based on our selected model, the significance of TNSC's effect in predicting the risk of IM is justified with a p-value less than 10 − 6 . We also select the most appropriate mixed-link models (Models 2 and 3) when an additional covariate, the status of gastric atrophy, is available. When the status is negative, mild, or moderate, we recommend Model 2; otherwise, we prefer Model 3. Both Models 2 and 3 can predict the risk of IM significantly better than Model 1, which justifies that the status of gastric atrophy is informative in predicting the risk of IM. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Map matching of trajectory data has wide applications in path planning, traffic flow analysis, and intelligent driving. The process of map matching involves matching GPS trajectory points to roads in a roadway network, thereby converting a trajectory sequence into a segment sequence. However, GPS trajectories are frequently incorrectly matched during the map-matching process, leading to matching errors. Considering that few studies have focused on the causes of map-matching errors, as well as the distribution of these errors, the study aims to investigate the spatiotemporal characteristics and the contributing factors that cause map-matching errors. The study employs the Hidden Markov Model (HMM) algorithm to match the trajectories and identifies the four types of map-matching errors by examining the relationship between the matched trajectories and the driving routes. The map-matching errors consist of Off-Road Error (ORE), Wrong-match on Road Error (WRE), Off-Junction Error (OJE), and Wrong-match in Junction Error (WJE). The kernel density method and multinomial logistic model are further exploited to analyze the spatiotemporal patterns of the map-matching errors. The results indicate that the occurrence of map-matching errors substantially varies in time and space, with variation significantly influenced by intersection features and road characteristics. The findings provide a better understanding of the contributing factors associated with map-matching errors and serve to improve the accuracy of map matching for commercial vehicles. [ABSTRACT FROM AUTHOR]

Rural livelihood diversification has become a central policy in rural development and poverty alleviation. Farmworkers in irrigation schemes are a typical poor sub-group that has received little attention in research regarding their livelihood status and the contribution of diversification. This paper provides evidence derived from a study that was carried out to examine whether farmworkers in the study area diversify their livelihoods and identify their choices of livelihood-diversification strategies and the determinants thereof. Data were collected from 191 randomly selected farmworkers and analyzed using the binary probit model and the multinomial logistic model. Variables considered in the binary probit model—gender, number of dependents, employment type, farming experience, land leasing, and market access—influenced livelihood diversification among irrigation farmworkers in a statistically significant way. The multinomial logistic model analysis considered age, marital status, household dependents, leasing land from employer, farming experience, agricultural training, and access to markets as the statistically significant factors that influence the choice of livelihood-diversification strategies in the study area. The study concluded that rural development policies should consider leasing land to irrigation farmworkers that is adequate to reduce poverty, achieve food security, and sustain the livelihoods of farmworkers in the study area, as it boosts the generation of income. [ABSTRACT FROM AUTHOR]

After 2020, poverty alleviation in China will shift from eliminating absolute poverty to alleviating unbalanced and insufficient relative poverty. Based on Amartya Sen's capability approach, this article aimed to realize the freedom of "capability" of children and ensure the well-being and development of Chinese adolescents, who are often ignored in child poverty research. The study sought to estimate the 10–15-year-olds in a multidimensional capabilities poverty group. Our analysis was based on the adolescent capability methodology framework, using data from the 2018 China Family Panel Studies (CFPS) to investigate the types and influencing factors of adolescent capability poverty in China. The result of latent class analysis showed that there are four types of capability poverty among the Chinese adolescents, namely, Extreme Capability Poverty Class, Goal Capability Poverty Class, Opportunity Capability Poverty Class, and Capability Non-Poverty Class. Multinomial logistic regression showed that the personal factors of gender, ethnic minority, hukou, and pocket money; the family factors of parents' marital status, parents' education level, and region of residence; and the family economic factor of per capita family income had a significant impact on the types of China's adolescent capability poverty. The article provides empirical and quantitative evidence for the adolescent (ages 10–15) class of capability poverty. The findings provide a reference for policy makers to target poverty-alleviation efforts according to different types of poverty and to interrupt the intergenerational transmission of poverty. [ABSTRACT FROM AUTHOR]

Wildfires are a common disturbance event in the Canadian boreal forest. Within event boundaries, the level of vegetation mortality varies greatly. Understanding where surviving vegetation occurs within fire events and how this relates to pre-fire vegetation, topography, and fire weather can inform forest management decisions. We used pre-fire forest inventory data, digital elevation maps, and records of fire weather for 37 naturally-occurring wildfires (1961 to 1982; 30 to 5500 ha) covering a wide range of conditions in the western Canadian boreal forest to investigate these relationships using multinomial logistic models. Overall, vegetation mortality related to a combination of factors representing different spatial scales. Lower vegetation mortality occurred where there was lower fuel continuity and when fires occurred under non-drought conditions. Higher classification accuracy occurred for class extremes of no mortality (i.e., unburned areas within the burn event) and high mortality; partial vegetation mortality classes were harder to distinguish. This research contributes to the knowledge required for natural pattern emulation strategies, and developing responses to climate change. [ABSTRACT FROM AUTHOR]

In recent years, app-based third taxi service (ATTS) and free-floating bike sharing (FFBS) have become significant travel modes to satisfy travel demands of urban residents. In order to explore the mechanism of their modes selection, firstly, based on 595 valid samples, differences between ATTS and FFBS in original modes, travel distance, geographical position distribution, and travel emergency degree were compared. Then, a multinomial logistic model was established to investigate the factors influencing the choice among ATTS, FFBS, and traditional travel modes (TTM). The results show that: (1) FFBS attracts users whose original modes are walking, private bicycle and bus, while ATTS has a certain competition effect on cruising taxi and bus. (2) Residents are more likely to change from bus to FFBS on weekends, while this competitive relationship between ATTS and bus has no significant difference in different dates. (3) Compared with TTM, residents are more inclined to utilize shared modes to participate in flexible activities, especially in suburb. (4) Interestingly, ATTS is more likely to be utilized in emergency travel, and the residents without registered permanent residences tend to use FFBS and ATTS. Finally, some suggestions and policies were proposed for the government and enterprises to improve operation managements. [ABSTRACT FROM AUTHOR]

To achieve a balance between agricultural production and environmental protection, organic farming has long been viewed as an alternative for sustainable agricultural development. This study aims to determine the key factors influencing the distribution of organic rice cultivation. Using a unique dataset for the production and environmental characteristics of organic farmland and operations, we assess the impact of spatial clusters, namely cold, hot, and neutral spots, on the certified areas of organic rice. Then, combining the local indicators of spatial association and a multinomial logistic model, we reveal that organic farming is likely to occur in agriculturally less-favored regions, and that improvements in natural productivity is not a favorable incentive for farmers to expand their certified areas. For hot spots, an efficient approach to expand the development of organic farming or certified areas is to increase the scale of agricultural production and marketing groups or even the proportion of individual farmers in operational patterns. Our findings have policy implications for the selection of special regions for organic farming in Taiwan. Further, the analysis of marginal effects provides insight on raising the effectiveness of agricultural sustainability policies. [ABSTRACT FROM AUTHOR]