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Most studies that address the integration of active modes (i.e., walking and bicycling) and public transit tend to focus on either transfer distance or feeder mode choice. Few articles have reported the relationships between the built environment (D-variables) and transfer patterns (e.g., transfer distance and mode choice) in a single study. Furthermore, only very few studies accounted for travelers’ judgements of walkability and/or bikeability and distinguished between access and egress trips. This paper fills these gaps in the literature using data collected in Nanjing, China. A random parameter Tobit and a random parameter multinomial logistic model are estimated to investigate respectively (i) the association of perceived walkability/bikeability and features of the built environment in metro catchment areas on walking/bicycling distance of access/egress trips and (ii) the probability of choosing active modes as transfer modes. The modeling results reveal that perceived walkability/bikeability and features of the built environment are more significantly correlated with mode choice behavior than with transfer distance. Moreover, walking/bicycling distance and access/egress mode choice tend to be strongly associated with perceived walkability and bikeability as well as with features of the built environment. The results are helpful in deepening urban planners and policymakers’ understanding of how to design built environments that maximize the integration of active modes and metro.

The happiness levels of individuals and their sources of happiness have been wondered a lot and researched from past to present. The aim of this study is to examine the factors that affect individuals' sources of happiness. The data set of the study was obtained from the Life Satisfaction Survey of the Turkish Statistical Institute. 9212 individuals were included in the study. In the study, chi-square independence tests were conducted to examine the relationship between the source of happiness and the independent variables included in the model, and multinomial logistic regression analysis was applied to determine the factors that may have an effect on the sources of happiness of individuals. As a result of the study, it has been determined that the factors of the individual's age, gender, marital status, educational status, satisfaction with income level, welfare level, life satisfaction, satisfaction with a social life are effective on sources of happiness. At such a time when it is clear that the coronavirus epidemic adversely affects many aspects of our lives, especially our psychology, and will leave a mark on our tomorrows, and the activities of decision-makers and policymakers are shed light through the study in order to increase the happiness of individuals and to ensure that the future will be better.

Separation or monotone-likelihood can be observed in fitting process of a multinomial logistic model using maximum likelihood estimation (MLE) when sample size is small and/or one of the outcome categories is rare and/or there is one or more influential covariates, resulting in infinite or biased estimate of at least one regression coefficient of the model. This study investigated empirically to identify the optimal data condition to define both ‘separation’ and ‘near-to-separation’ (partial separation) and explored their consequences in MLE and provided a solution by applying a penalized likelihood approach, which has been proposed in the literature, by adding a Jeffreys prior-based penalty term to the original likelihood function to remove the first-order bias in the MLEs of the multinomial logit model via equivalent Poisson regression. Furthermore, the penalized estimating equation (PMLE) is extended to a weighted estimating equation allowing for survey-weight for analyzing data from a complex survey. The simulation study suggests that the PMLE outperforms the MLE by providing smaller amount of bias and mean squared of error and better coverage. The methods are applied to analyze data on choice of health facility for treatment of childhood diseases.

Summary This paper focuses on pragmatic competence development in second or foreign language learners. In particular, it attempts to fill the significant research gap in measuring change in pragmatic competence and capturing pragmalinguistic and sociopragmatic development over time. The paper proposes an innovative approach by applying a logistic model with multinomial distribution for measuring change in InterLanguage Pragmatics Research (ILP). Applied in the field of pragmatics, this statistical tool offers a comprehensive and flexible approach to modelling relations between independent and dependent variables in ILP research. The model is tested in a longitudinal study of Polish undergraduate students learning English, and specifically in the way they formulate requests by means of requestive directness strategies. The paper concludes that, regardless of time elapsing, the factors P (power distance) and D (social distance) have a highly significant influence on the use of requestive directness strategies by Poles learning EFL. Furthermore, the analysis indicates that the pragmatic output of Poles learning EFL is dependent on one more independent variable: the estimation of future social distance (F).

This study investigated the Effect of Levels of Education on the Choice of Medical Treatment Options for three illnesses (Malaria, Mental Disorder and HIV/AIDS) in Nigeria. The study was carried out in ten randomly selected Local Government Areas (L. G. As) in Imo State using a stratified random sample of 500 individuals selected from a population of 194,932 and the data was collected using questionnaires. The Multinomial Logistic Regression Model was adopted in the analysis of the data. The result of the analysis showed that there was a significant association between Educational Level and choice of treatment of Malaria, Mental Disorder and HIV/AIDS. It was further discovered that it is only the “WAEC/GCE” level of education that is significant in the Choice of Treatment of Mental Disorder. It is therefore recommended that government should beam its searchlight on this educational level to find out the cause(s) of their Mental Disorder.

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.

In this article, we propose a two-way multinomial logistic model for recommender systems for categorical ratings. Specifically, we treat the possible ratings as mutually exclusive events, whose pro...

There has been an extensive tradition of geographical studies7 conducted to analyse the access to urban parks or green spaces. Several studies deploy approaches to measure the potential spatial accessibility and congestion of children’s playgrounds in urban areas. Identifying inequalities in terms of spatial access to children’s playgrounds is an important issue that could be useful for urban planners. The main objective of this paper is to measure the potential spatial accessibility and congestion of playgrounds in Barcelona City. A second objective is to analyse the factors that may explain differences between neighbourhoods in spatial access to playgrounds. Several analyses were carried out. First, two indicators of spatial potential accessibility are computed at the census tract level. Next, a mapping technique is used based on a cross tabulation of the quintiles of two indicators. A typology of census tracts can then be developed according to the various possible combinations between playground accessibility and congestion. Third, two spatial models—spatial lag and spatial error—are estimated in order to introduce socioeconomic factors into the explanation of accessibility and congestion. Finally, a multinomial logistic model is estimated to explain the typology of Barcelona census tracts based on potential playground congestion and accessibility. The results show that in Barcelona City, there are no important spatial disparities in terms of access to children’s playgrounds.

Landing price variations as a result of its determinations impact fishers’ subjective wellbeing. This paper presents an analysis of the fish landing price effect on the subjective wellbeing of fishers around Lake Victoria, Tanzania. A cross-sectional study was carried out from the sample size of 289 of artisanal fishers. The multinomial logistic model employed to examine the effects of the landing price on the subjective wellbeing of fishers. This study found that landing price positively influenced subjective wellbeing satisfaction of fishers given that, often and all the time during landing, the landed price of fish is determined by fishers and negatively influencing subjective wellbeing of fishers for the rarely and some of the time this landing price is determined by fishers. This study concluded that there is a significant change on the subjective wellbeing of fishers with significant changes in the landing price in the way it is determined by fishers around Lake Victoria, Tanzania. It is recommended action to be undertaken by fishers to reduce rarely and some of the time, capability in determining landing price in order to minimize negative feelings on landing price received by fishers. This can be done through a collective agreement between fishers’ cooperative framework, a room for provisions of pricing skills among artisanal fishers and buyers.

European countries differ greatly in the proportions of people who receive various types of care. They also differ considerably regarding the societal characteristics of care such as the availability of formal care within the country. We explored the explanatory potential of contextual characteristics of the provision of formal home care, and barriers to using long-term care services for older people’s care arrangements across Europe. We employed data from Wave 5 of the Survey of Health, Ageing and Retirement in Europe, and analyze the data using a multinomial logistic model. Less involvement and lower national governance in the integration of home care policy decreases the use of formal care alone, and in combination with informal care. Higher integration and coordination in delivering home-care services increases the use of formal services. In countries with higher shares of reported barriers to using their long-term care systems there is a smaller probability of formal services being used.

The Philippines has recently been aiming to achieve self-sufficiency in rice. Recent programs and policies have been anchored on the development and adoption of high-yielding rice varieties in order to achieve this goal. Thus, this paper aims to identify the factors that significantly affect the farmers’ adoption of high-yielding varieties such as hybrid and certified inbred rice. Using a multinomial logistic model, these factors were estimated. Results show that the age, input assistance, and collective marketing significantly affect the adoption of certified inbred rice over farmers’ recycled seeds. On the other hand, irrigation, farm size, and trainings significantly affect the adoption of hybrid over farmer’s recycled seeds. In general, there was a low adoption rate of hybrid rice. Key informant interviews revealed that several issues arise in the process of seed growing, production, and marketing. Therefore, to increase the farmers’ incentive to adopt hybrid rice, a hybrid variety that produces superior grain quality and resistance to stresses must be developed and distributed at a reasonable price.

The emergence of free-floating bike sharing (FFBS) has made essential changes in urban bicycle travel. In order to explore the differences of travel behavior among private bicycle (PB), public bicycle sharing (PBS) and FFBS, a survey was conducted in Kunming, China in 2018. Firstly, the differences of travel characteristics among these three modes were analyzed based on 522 valid questionnaires. Then, a multinomial logistic model was applied to explore the influential factors among them. The results show that: 1) PB and FFBS are more attractive for long-distance travel enthusiasts compared with PBS, PB is rarely used for transfer in suburbs while FFBS is the most desirable in connecting other travel modes. The theft problem and high maintenance costs are main obstacles for PB. 2) The elderly, high-income and non-student groups in inflexible travel activities show a preference for PBS, while the young, low-income and student groups in flexible travel demands have a tendency towards FFBS. 3) PB and PBS imped the use of FFBS to a certain extent, while PB seems to have less impact on PBS. 4) FFBS is desirable in temporary travel demand while PBS is more preferable in fixed demand. Interestingly, residents with registered permanent residence tend to use PBS while those without registered permanent residence prefer FFBS. Finally, several management strategies and policy recommendations were proposed for the government and FFBS enterprises to improve the management of bicycles.

The study examines the impact of Micro Hydropower (MHP) projects on households’ income, consumption and diversification of livelihood strategies in District Hattian Bala, Azad Jammu and Kashmir. A multinomial logistic model is used to investigate the possible role of MHP and other control variables on households’ adoption of livelihood strategies. The Results show that MHP-micro hydropower has a positive significant effect on household’s adoption of non-farm and diversified livelihood strategies. These findings suggest that MHP projects in Northern areas of Pakistan could help in improving household’s income and consumption through adoption of high income livelihood strategies. Keywords: Micro Hydropower (MHP), Livelihood Strategies, Income and Expenditures, Poverty Alleviation, Multinomial Logistic Model

In this study we aim at assessing the willingness to invest of small‑apple farms in Korça region‑Albania. Furthermore, we want to identify and assess what are major determinants, as percept by farmers’, willingness to invest. To this purpose we used data collected through face‑to‑face interviews with apple farmers. We used descriptive statistics, as well as classical and multinomial logistic regression. Most of farmers are willing to invest in view of their positive expectations for investment climate. Other important factors of willingness to invest are access to loans, advisory extension services, market competition, willingness to cooperate and willingness to take loans, and farm income, while socio‑demographic factors such as age, education, and farming experience do not have significant effect on willingness to invest. Large farms are generally more willing to invest. We present also a general framework of constraints and policy levers to improving the investment climate which is almost valid also for Albania. Improving farmers’ access to private credit sources, policy stability, providing information and public advisory services to small farmers, support farmers to adopt new technology, support to the creation of farmers’ formal and informal groups, and mitigate risks of various type are some but essential policy measures to motivate farmers to invest more in apple.

The economic circumstance of a household is in most cases linked to the varied situations a household may find itself income is to a greater extent linked to the housing and food that a household is exposed to. Income among other socio-economic factors may also affect the demand structure of the household in terms of what the household may consider necessary or not. The level of household demand for health services and its preventive level may also be associated with other household characteristics especially those associated with the head of the household. This paper analysed the relationship between the morbidity rate in a household and the household characteristics and the characteristics of the head of household. The paper uses data collected in the South African general household survey published in 2017 conducted by Statistics South Africa. Based on a sample of 21601 households, the study employs a multinomial logistic model with the level of morbidity rate categorised into a high level, mild, and low. The results of the empirical analysis show that Household size, the gender of head of household, housing insecurity status age of head of household and income were significant determinants of morbidity rate at the household level. The contribution of the paper is therefore a proposal for preventive mitigation as opposed to treatment which tends to be more expensive on government. The fact that housing insecurity is a competing need with health demand calls for better alignment in terms of government, provision of health services in South Africa. This paper is motivated by the initiative of the introduction of a national health Insurance (NHI) is South Africa.

China is a country with a unique history of gender traditions and birth-control regulations. Traditional gender role attitudes, closely related to son preference, exert entrenched influence on the ...

The growth in personal Internet use for the purposes of communication, shopping and documentation has the potential to reduce travel by substituting trips with on-line activities. Evidence suggests that on-line communications have mild impact on travel as face-to-face communications are still favored and on-line shopping is often supplemented with in-store shopping. On-line media and documentation use also typically supplement traditional media. Internet use may rather be a complement to travel related activities. This paper explores Internet use for these three purposes and evaluates associations with overall travel and travel for these specific purposes. The 2010 Canadian General Social Survey provides a one-day time use diary including Internet-based and travel activities. Three categories of home-based Internet activities (communication, shopping and media and documentation) can be associated with related trip purposes. A Multinomial Logistic model of Internet use intensity explores the socioeconomic drivers of Internet use for workers and students (n = 8239). Associations between Internet use and time spent traveling (overall and purpose specific, Tobit models) and trip frequencies during the survey day (negative binomial models) are then assessed. Heavy Internet use is associated with reduced overall travel time but with variations in travel time and number of trips for purposes directly related to Internet activities. On-line shopping was positively associated with travel for shopping. On-line personal communication was negatively associated with travel for communication. Distinction in purposes of Internet use and in targeted population groups will be required to elaborate policies more likely to reduce travel as a result of Internet use.

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.

Objective Psychosocial factors, such as environmental stressors, can increase the risk of hypertension. This study examines the role of the household environment in hypertension outcomes by assessing the link between female hypertension status and spousal alcohol consumption in Nepal. Study design This is a cross-sectional study. Methods We used the 2016 Nepal Demographic and Health Survey to assess differences in hypertension outcomes in women aged 15 to 49 years whose husbands drink alcohol and in those whose husbands do not. We estimated a multinomial logistic model to obtain adjusted differences in the likelihood of being hypertensive between the two groups. We also examined several socio-economic conditions across the two groups to discuss various aspects of the association. Results After controlling for anthropometric and various sociodemographic attributes, we find that women whose husbands drink alcohol were 2.5 percentage points (95% confidence interval [CI]: −0.31, 5.31) more likely to be hypertensive than women whose husbands do not. They were also more likely to experience food insecurity, to experience spousal violence, and to consume tobacco products. Among women whose husbands became intoxicated (‘got drunk’) very often, the likelihood of being hypertensive was 4.0 percentage points (95% CI: −0.26, 7.67) higher than among women whose husbands do not drink alcohol. Conclusion Women whose husbands consume alcohol have an elevated risk of being hypertensive, illustrating the association between hypertension and the household environment. The findings document the added hypertension burden in socially vulnerable population groups and can inform initiatives to reduce alcohol consumption in Nepal.

This present study explores the drivers of tourism demand of potential tourists to Korea in Vietnam who have the different level of cultural proximity about South Korea. This study segmented respondents in Vietnam based on cultural proximity to understand the potential Hallyu tourism market. The data was collected through an online survey linked on Facebook from December 2017 to March 2018 and a total of 379 respondents were used for final analysis. Three cultural proximity factors were used as composite variables to classify the respondents into similar groups, and three segments were found. On the basis of the estimates from this model, the demographic characteristics, travel related characteristics, and Hallyu tourism motivations and effects are compared among the three segments by using a multinomial logistic model. The results of this study provide several theoretical and practical implications.

This study investigates whether firm dividend payout choices are influenced by the presence of a Dividend Reinvestment Plan (DRIP). Given that DRIPs help retain capital, we show that dividend‐paying firms with a DRIP will tend to pay a high dividend and maintain a stable payout policy. Using a multinomial logistic model, we show that in comparison to REITs without DRIPs, REITs with DRIPs have a higher payout ratio and are less likely to: (1) pay regular dividends with extra dividends and share repurchases, (2) distribute extra dividends, repurchase shares, yet omit regular dividends and (3) omit all payouts. In addition, we find that REITs with a capital‐retaining DRIP invest more aggressively and such increased investment activities are undertaken without raising the reliance on external financing.

This paper is aimed at studying the inter-enterprise relations in Italy focusing on territorial differences. A multinomial logistic model is proposed to estimate the effects of a set of relevant business characteristics on the propensity to relations, using official data sources. The results show which are the most relevant factors associated with the relational behavior (i.e. sector of economic activity, introduction of innovations, level of revenues from sales), proving that the impact of the territorial dimension turns out to be significant, albeit rather limited. The business characterization arising from the model may be useful to policy formulation.

This paper examines the major socioeconomic and demographic determinants of rural households’ saving behavior in Sinana district, Ethiopia. A random sample of 267 rural households was selected from four rural kebeles of the district. The study used both descriptive statistics and econometric model for the analysis of primary data. The result of descriptive statistics demonstrates that 47.2% of the sampled households preferred formal saving, 33.3% preferred informal saving and 19.5% preferred both formal and informal saving behaviors, respectively. Econometric result confirms that the probability of preferring informal saving increases with increase in access to credit and distance from formal financial institution, and decreases with increase in square root of annual total income as compared to preferring formal saving behavior. Similarly, the probability of preferring both formal and informal saving behaviors increases with increase in the tropical livestock holding, and decreases with increase in land size as compared to preferring formal saving behavior. Therefore, these variables need special attention in addition to the intervention of concerned authority if the saving behavior of rural households is to be improved. Key words: Multinomial logistic model, households, saving behavior, Sinana district.

Regularized multinomial logistic model is widely used in multi-class classification problems. For high dimension data, various regularization methods achieving sparsity have been developed and applied successfully to many real-world applications such as bioinformatics, health informatics and text mining. In many cases there exist intrinsic group structures among the features. Incorporating the group information in the model can enhance model performance. In multi-class classification, different classes may relate to different feature groups. With these considerations, we propose a class-conditional regularization of the multinomial logistic model (CCSOGL) to enable the discovery of class-specific feature groups. To solve the model, we developed an efficient cyclic block coordinate descent based algorithm. We also apply our method to analyze real-world datasets to demonstrate its superior performance.

The aim of this study was to investigate the levels and determinants of unwanted pregnancies and therapeutic and elective induced abortions in an Iranian sample of women. This study was conducted from the beginning of 2013 to the end of July 2013, using data from 950 women aged 15-45 years. To evaluate the relationship of independent variables to the number of unwanted pregnancies, a negative binomial regression model was used. A multinomial logistic model was used to investigate the relationship of the history of at least one unwanted pregnancy to therapeutic and elective induced abortion. The prevalence of unwanted pregnancy among participants was 19.2 percent (n = 182). Among those with a history of unwanted pregnancy, eighteen had had at least one induced abortion (14.5 percent of the total abortions reported). Having enough knowledge about the intrauterine device during unprotected intercourse on average was associated with a 57 percent reduction in unwanted pregnancies (mean odds ratio = 0.43, 95 percent Confidence Interval (CI): 0.11-0.93). Given the high rates of complications following unwanted pregnancies and associated maternal health threats, timely identification and training of women at risk, as well as the development of appropriate attitudes regarding reproductive health, may help avoid such pregnancies and their complications.

With ongoing urban revolution, Chinese cities are experiencing an influx of migrants, whose integration into urban society becomes an unprecedented challenge. Using a recent survey in Shanghai and adopting a multilevel multinomial logistic model, this paper studies perceptions of social integration, comparing local residents with migrants. While migrants and local residents have very different perceptions of social integration, both individual-level factors and community-level factors such as residential segregation shape perceptions of social integration, and they shape migrants and local residents differently. In particular, residential segregation, especially migrant population size, tends to reinforce perceptions of social exclusion, which imposes challenges on social integration.

This study engaged the Multinomial Logistic Model (MLN) to determine factors influencing te choice of coping strategies of diabetic yam farming households in Benue State, Nigeria. A multi-stage random sampling technique was used to select 340 yam farming households with emphasis on 2015 farming season. Primary data were obtained using a well structured and pretested questionnaire. The results of analysis shows that the most frequently used coping strategies were special diets such as millet, cocoyam, locust bean, groundnut, fruits and vegetables accounting for 39%, constant intake of drugs like metformin, biguarnide, sulphorylureas and insulin 25%, hired labour, 23.2%, routine exercise, 12.6%, while hawking was 0.3%. The choice of constant drug was -0.012, while the choice of hawking was significantly (p < 0.05) and negatively affected by education as a coping strategy. The marginal effect of education on constant drug was -0.012, while the choice of hawking was significantly (p < 0.05) and positively affected by the age as a coping strategy. The marginal effect of age on hawking was 0.04. It is recommended that government at Federal, State and Local levels with partners in progress should consider critical ways of managing diabetes by emphasizing healthy lifestyles such as ceasation of smoking, moderate alcohol intake, regular medical check-up and improvement of the socio-economic status of the diabetic farm households through good road network, steady supply of electricity which will better the quality of life of the farm households.

Background: The main goal of this study was to diagnose the two most common thyroid disorders, namely, hyperthyroidism and hypothyroidism, based on multinomial logistic regression and neural network models. In addition, the study evaluated the predictive ability of laboratory tests against the individual clinical symptoms score. Materials and Methods: In this study, the data from patients with thyroid dysfunction who referred to Imam Khomeini Clinic and Shahid Beheshti Hospital in Hamadan were collected. The data contained 310 subjects in one of three classes—euthyroid, hyperthyroidism, and hypothyroidism. Collected variables included demographics and symptoms of hypothyroidism and hyperthyroidism, as well as laboratory tests. To compare the predictive ability of the clinical signs and laboratory tests, different multinomial logistic regression and neural network models were fitted to the data. These models were compared in terms of the mean of the accuracy and area under the curve (AUC). Results: The results showed better performance of neural network model than multinomial logistic regression in all cases. The best predictive performance for logistic regression (with a mean accuracy of 91.4%) and neural network models (with a mean accuracy of 96.3%) was when all variables were included in the model. In addition, the predictive performance of two models based on symptomatic variables was superior to laboratory variables. Conclusions: Both neural network and logistic regression models have a high predictive ability to diagnose thyroid disorder, although neural network performance is better than logistic regression. In addition, as achieving less error prediction model has always been a matter of concern for researchers in the field of disease diagnosis, predictive nonparametric techniques, such as neural networks, provide new opportunities to obtain more accurate predictions in the field of medical research.

In tropical regions, populations continue to suffer morbidity and mortality from malaria and arboviral diseases. In Kedougou (Senegal), these illnesses are all endemic due to the climate and its geographical position. The co-circulation of malaria parasites and arboviruses can explain the observation of coinfected cases. Indeed there is strong resemblance in symptoms between these diseases making problematic targeted medical care of coinfected cases. This is due to the fact that the origin of illness is not obviously known. Some cases could be immunized against one or the other of the pathogens, immunity typically acquired with factors like age and exposure as usual for endemic area. Thus, coinfection needs to be better diagnosed. Using data collected from patients in Kedougou region, from 2009 to 2013, we adjusted a multinomial logistic model and selected relevant variables in explaining coinfection status. We observed specific sets of variables explaining each of the diseases exclusively and the coinfection. We tested the independence between arboviral and malaria infections and derived coinfection probabilities from the model fitting. In case of a coinfection probability greater than a threshold value to be calibrated on the data, long duration of illness and age are mostly indicative of arboviral disease while high body temperature and presence of nausea or vomiting symptoms during the rainy season are mostly indicative of malaria disease.

Data from the 2011–2012 National Survey of Children’s Health and the 2013 National Survey of Children in Nonparental Care were used to fit a multinomial logistic model comparing three groups to those who never considered adoption: those who ever considered, but are not currently planning adoption; those planning adoption; and those who adopted. Adoption may be more likely when the caregiver is a nonkin foster parent, a foster care agency was involved, and/or financial assistance is available. Those with plans to adopt but who have not adopted may face adoption barriers such as extreme poverty, lower education and being unmarried.

The aim of this study was to identify the factors that actually guide people’s decision regarding kind of health care service chosen for outpatient treatment in rural Assam. For that, primary data have been collected from the rural areas of Goalpara as it is one of the representative districts of Assam. A total of 281 households were selected through multistage sampling in which 122 cases were found, where outpatient health care was utilized during the 30-day reference period. Bivariate analysis has been done in terms of Pearson’s correlation coefficient to see the relation between the explanatory variables and response variable. Further, multinomial logistic model has been used to find the factors responsible for people’s diverse choice regarding the utilization of outpatient health care. This study has identified the economic condition of the rural household which the patient belongs to; the level of education of the patient herself and severity of ailment are the major factors which actually guides the decision regarding the utilization of outpatient health care in rural Goalpara.

The present study investigated (a) comparisons in rates of rape and sexual assault acknowledgment and (b) a comprehensive multivariate multinomial logistic model predicting rape and sexual assault acknowledgment in a sample of 174 college women who had experienced rape. Significantly more women acknowledged having experienced sexual assault than rape. Greater perceived perpetrator force was associated with increased likelihood of rape and sexual assault acknowledgment. Increased age and greater perceived emotional impact were associated with increased odds of rape acknowledgment. Implications for policy, education, and practice within university settings are discussed.

With the developing trends of commercialization of agriculture, the magnitude of loss due to unfavorable eventualities is increasing and the farmers committed suicides. Burdwan district of West Bengal, India, becomes news headline because of farmer suicide. This study tries to underscore the elements which impact marginal farmers’ decision to accept Pradhan Mantri Fasal Bima Yojona (PMFBY). We collect primary data from 701 farmers in the study over period of from February 2017 to October 2017. Seven estimators, namely education, age, cultivating land area, self-help groups (SHGs), marital condition, gender, and income, are considered, and multinomial logistic regression was used to analyze the data. Results show that gender coefficient is negative which indicates female farmer are prone to agro insurance (access to PMFBY) than male farmers. Results indicate that farmers’ PMFBY and income are significant to the situation that one applies if others apply and get benefit.

Environmental and community factors may influence the development or course of depression and sleep problems. We evaluated the association of unconventional natural gas development (UNGD) with depression symptoms and disordered sleep diagnoses using the Patient Health Questionnaire-8 and electronic health record data among Geisinger adult primary care patients in Pennsylvania. Participants received a retrospective metric for UNGD at their residence (very low, low, medium, and high) that incorporated dates and durations of well development, distance from patient homes to wells, and well characteristics. Analyses included 4,762 participants with no (62%), mild (23%), moderate (10%), and moderately severe or severe (5%) depression symptoms in 2014–2015 and 3,868 disordered sleep diagnoses between 2009–2015. We observed associations between living closer to more and bigger wells and depression symptoms, but not disordered sleep diagnoses in models weighted to account for sampling design and participation. High UNGD (vs. very low) was associated with depression symptoms in an adjusted negative binomial model (exponentiated coefficient = 1.18, 95% confidence interval [CI]: 1.04–1.34). High and low UNGD (vs. very low) were associated with depression symptoms (vs. none) in an adjusted multinomial logistic model. Our findings suggest that UNGD may be associated with adverse mental health in Pennsylvania.

This paper analyses tourism demand in the tourist districts in Sicily to study the relationship between the characteristics of tourists, types of tourism and expenditure. The data were obtained from a survey of tourists leaving the island after a holiday. The likelihood of choosing a type of holiday is estimated by means of a multinomial logistic model. The findings highlight the importance of the seaside, cultural, and food and wine/nature segments. The analysis of the distribution of per capita per day expenditure shows higher average values for the cultural holiday. The research provides insights for decision makers concerning the implementation of destination market strategies.

Cancer patients may die from causes other than the diagnosed cancer. In a study of patients treated for soft tissue sarcoma, the patients may die from the disease or die without experiencing disease recurrence. In addition, a substantial proportion of the patients will remain cancer-free after surgical resection of the tumour, and therefore will not be at increased risk of any type of failure. Our goal is to describe the effect of adjuvant chemotherapy simultaneously on the probabilities of long-term survival, death from cancer, or death from other causes. To this end, we propose a semiparametric mixture model to determine the effects of factors on the probability of occurrence, allowing the surviving fraction, and the hazard rate conditional on each of the failure types. These quantities are combined in the mixture approach using a multinomial logistic model and a class of semiparametric transformation models. Estimation of the regression and nonparametric parameters is achieved with a novel nonparametric maximum likelihood approach. Statistical inferences can be conveniently made from the inverse of the observed information matrix. Simulation studies show that the procedures work well in practical settings. The methodology is illustrated with data from the soft tissue sarcoma study. The Canadian Journal of Statistics 43: 420–435; 2015 © 2015 Statistical Society of Canada Resume Les patients atteints du cancer peuvent aussi mourir d'une autre cause. Dans une etude sur les sarcomes des tissus mous, certains patients decedent de la maladie et d'autres meurent sans connai tre de rechute. De plus, une proportion importante des patients demeurent sans traces du cancer apres une resection de la tumeur et ne sont ainsi soumis a aucune augmentation de risque. L'objectif des auteurs consiste a decrire simultanement les effets d'une chimiotherapie adjuvante sur les probabilites de survie a long terme, de mort due au cancer et de mort due a une autre cause. A cette fin, les auteurs proposent un modele semi-parametrique de melange pour determiner les effets de differents facteurs sur les probabilites de ces evenements, utilisant une fraction de survie et un niveau de risque conditionel a chacun des types d’evenement. Ces quantites sont combinees dans le melange a l'aide d'un modele logistique multinomial et une classe de modeles de transformation semi-parametriques. Les auteurs estiment les parametres de la regression et les elements non parametriques par une nouvelle approche basee sur une vraisemblance non parametrique. L'inverse de la matrice d'information observee permet de proceder a l'inference statistique. Les auteurs presentent des etudes de simulation qui montrent que la procedure fonctionne bien dans des situations pratiques. Ils illustrent egalement leur methode a l'aide de donnees d'une etude sur les sarcomes des tissus mous. La revue canadienne de statistique xx: 1–16; 2015 © 2015 Societe statistique du Canada

This paper investigates the contagion risk for Australian-owned authorised deposit-taking institutions ( ADIs) spilling from the US and UK banks. We hypothesised that Australian ADIs are prone to extreme shocks experienced by their US and UK counterparts. We define four discrete events for the Australian banking sector in terms of the number of banks exceeding an extreme value at some time. The extreme value is defined as the 90th percentile on the negative tail of the distribution of changes in the distance to default obtained through the Black-Scholes-Merton formula. Then we fit a multinomial logistic model ( MLM) to relate these events to the number of exceedances (extreme events) occurring in the US and the UK in the previous day for the time period from September 2006 to September 2011. The MLM estimates reveal strong contagion effects for Australian ADIs from the US and UK banks.

This paper explores the interrelationship between trip chain pattern and trip mode choice based on multinomial logistic model, using 2010 Nanjing resident trip survey data. Unlike previous literatures, trip mode choice is divided into single-mode and multi-modes in this study. Estimation coefficients verify trip chain pattern and trip mode selection are a pair of choices that influence each other. Trip mode is great positively associated with trip chain pattern of HW+WH, HO+OH, HW+OH, however, in return trip chain pattern is the most significant negative factor that affects trip mode choice, which means that no trip chain pattern would provoke travelers to select multi-modes. Despite the results seem to reach a contradiction between trip chain pattern and trip mode choice, still two facets of views try to explain the phenomenon, in addition, discussion on the interrelationship between complex trip chain pattern and multi-modes which might put forward more challenges to urban planning is also proposed as well in the paper.

Understanding donor profiles is crucial for donor relationship management. Whereas previous research has focused on profiling blood, money, or time donor segments separately, we define seven donor profiles based on their former donation behavior for blood, money, and time donation and compare them to non-donors. Relying on representative data from the German Socio Economic Panel, we use an extensive set of characteristics that include sociodemographic, psychographic, health-related, and geographical measures and simultaneously investigate profiles of donors for single and multiple donation forms and non-donors by means of a multinomial logistic model. Our results reveal valuable insights for donor acquisition and retention strategies of nonprofit organizations along the identified profiling characteristics of donor segments. By this, our findings help nonprofit organization managers to better target single and multiple donors across three donation forms.

Summary Background Certain melanoma histotypes carry a worse prognosis than others. We aimed to identify patient related factors associated with specific melanoma histotypes. Patients and methods Single center study including 347 melanoma patients, prospectively assessed for 22 variables leading to a database of more than 7 600 features. Results Melanomas were histologically categorized as superficial spreading (SSM, 70.6 %), nodular (NM; 12.7 %), acrolentiginous (ALM; 4.0 %), lentigo maligna (LMM; 3.8 %), or unclassified melanoma (UCM; 8.9 %). Well recognized melanoma risk indicators (i. e. many atypical nevi, freckles, previous melanoma), were significantly associated with SSM and LMM histotypes. NM and ALM patients carried significantly less common and/or atypical nevi. NM were mostly self-detected or detected by relatives. In contrast, SSM, LMM, and ALM were most frequently detected by dermatologists. NM and UCM were preferentially located on poorly observable sites, SSM on the lower limbs, ALM on plantar sites, and LMM on the head and neck. ALM and LMM patients were significantly older than other patients. A multinomial logistic model was designed to predict a certain melanoma histotype (overall accuracy 81 %), which could be helpful to focus the attention of clinicians or may be integrated into fully automated diagnostic algorithms. Conclusions Melanoma histotypes show significant differences regarding patients’ characteristics.

Bat day-roost selection often is described through comparisons of day-roosts with randomly selected, and assumed unused, trees. Relatively few studies, however, look at patterns of multi-year selection or compare day-roosts used across years. We explored day-roost selection using 2 years of roost selection data for female northern long-eared bats ( Myotis septentrionalis ) on the Fort Knox Military Reservation, Kentucky, USA. We compared characteristics of randomly selected non-roost trees and day-roosts using a multinomial logistic model and day-roost species selection using chi-squared tests. We found that factors differentiating day-roosts from non-roosts and day-roosts between years varied. Day-roosts differed from non-roosts in the first year of data in all measured factors, but only in size and decay stage in the second year. Between years, day-roosts differed in size and canopy position, but not decay stage. Day-roost species selection was non-random and did not differ between years. Although bats used multiple trees, our results suggest that there were additional unused trees that were suitable as roosts at any time. Day-roost selection pattern descriptions will be inadequate if based only on a single year of data, and inferences of roost selection based only on comparisons of roost to non-roosts should be limited.

Traffic crashes are more likely to occur at intersections where the traffic environment is complicated. In this study, a hybrid approach combining cluster analysis and hierarchical Bayesian models is developed to examine driver injury severity patterns in intersection-related crashes based on two-year crash data in New Mexico. Three clusters are defined by K-means cluster analysis based on weather and roadway environmental conditions in order to reveal drivers' risk compensation instability under diverse external environment. Hierarchical Bayesian random intercept models are developed for each of the three clusters as well as the whole dataset to identify the contributing factors on multilevel driver injury outcomes: property damage only (Level I), complaint of injury and visible injury (Level II), and incapacitating injury and fatality (Level III). Model comparison with an ordinary multinomial logistic model omitting crash data hierarchical features and cross-level interactions verifies the suitability and effectiveness of the proposed hybrid approach. Results show that a number of crash-level variables (time period, weather, light condition, area, and road grade), vehicle/driver-level variables (traffic controls, vehicle action, vehicle type, seatbelt used, driver age, drug/alcohol impaired, and driver age) along with some cross-level interactions (i.e., left turn and night, drug and dark) impose significantly influence driver injury severity. This study provides insightful understandings of the effects of these variables on driver injury severity in intersection-related crashes and beneficial references for developing effective countermeasures for severe crash prevention.

The purpose of this study is to quantitatively evaluate the relationship between a longitudinal shock during braking of a train and ride comfort. The authors attempted to develop a method of quantitatively evaluating the main braking patterns envisaged (40 in total) with a view to establishing an evaluation method that would be readily applicable to actual driving and control. A multiple regression model and a multinomial logistic model were derived for a one-step braking process and the usefulness of same was confirmed on the basis of the high value of the coefficient of determination. Based on the model formula/formulae derived and the results of evaluating the braking patterns, it was possible to evaluate the 40 braking patterns by means of an ordinal scale. Train driving/control is evaluated with respect to various aspects from various perspectives, but the development of a method of evaluating ride comfort, which was partly unsolved, means that it is now possible to comprehensively evaluate train driving. Future application of the evaluation method in improving train-driving skills and in automatic train-driving controls can be expected.