Partial Proportional Odds Model Research Articles

Subjective perceived risk factors of exertional heat exhaustion-related symptoms in male collegiate athletes in Japan: a case-control study.

The purpose of this study was to investigate associations between lifestyle habits, health factors, athletic activity conditions, and exertional heat exhaustion (EHE)-related symptoms among male college athletes in Japan based on a self-completed questionnaire. The paper-based questionnaires were distributed to 11 universities in Japan, and 2006 respondents completed the survey. Data of personal characteristics (age, body mass), lifestyle habits (sleep duration, use of air-conditioner while sleeping, and practice duration), perceived health factors (loss of appetite, sleep deprivation, sickness, dehydration, accumulated fatigue, and mental stress), perceived athletic activity (insufficient rest breaks, high ambient temperature, excessive humidity, strong solar radiation, lack of ambient wind, and clothing discomfort), and EHE-related symptoms (dizziness, headaches, nausea, and malaise) were collected. The association between lifestyle habits, health factors, athletic activity conditions (explanatory variables), and EHE-related symptoms (objective variables) was analyzed using the partial-proportional odds model. "Perceived dehydration" (odds ratios [ORs] 1.70-2.31, p < 0.002)," "sickness" (ORs 1.35-1.76), p < 0.001), "perceived accumulated fatigue" (ORs 1.13-1.31, p ≤ 0.001), "perceived mental stress" (ORs 1.17-1.31, p < 0.019), "lack of ambient wind" (ORs 1.12-1.19, p < 0.022), "loss of appetite" (ORs 1.16-1.23, p < 0.037), and "sleep deprivation" (ORs 1.15-1.17, p < 0.025) were positively associated with EHE-related symptoms, whereas "using an air conditioner during sleeping" (ORs 0.91, p = 0.047) during summer seasons was negatively associated. These findings suggest that athletes should be allowed to postpone or downregulate exercise intensity and/or volume based on their perceptions of dehydration, sickness, accumulated fatigue, mental stress, loss of appetite, and/or sleep deprivation in the summer to prevent heat illness.

Determinants of nutritional status among primary school students in Dilla Town; Application of an ordinal logistic regression model

BackgroundOne of the most frequent reasons for children’s poor physical and mental development is malnutrition, becoming a more significant issue in most developing nations, including Ethiopia. Prior research used multiple anthropometric measurements separately to pinpoint undernutrition concerns in children. However, the impact of each explanatory variable on a single response category was not considered in these investigations. This study used a single composite index of anthropometric parameters to identify the factors affecting elementary school students' nutritional condition. MethodsIn Dilla, Ethiopia, 494 primary school students took part in a cross-sectional institutional survey during the 2021 academic year. Principal component analysis was used to create a single composite measure of nutritional status using z-scores for the anthropometric indices of height-for-age and body mass index-for-age. The relative effectiveness of a partial proportional odds model was compared with several other ordinal regression models to identify the important variables for children’s nutritional status. Results27.94% of primary school students were undernourished (7.29% severely and 20.65% moderately). According to the fitted partial proportional odds model, the mother’s education level (secondary or higher) was positively correlated with the nutritional status of primary school students, given that in this case the students ate three or more times per day and had a high dietary diversity score (OR = 5.94; CI: 2.2–16.0). Nevertheless, there was a negative correlation between larger family size (OR = 0.56; CI: 0.32–0.97), unprotected groundwater (OR = 0.76; CI: 0.6–0.96), and severely food insecure households (OR = 0.3; CI: 0.14–0.68). ConclusionIn Dilla, Ethiopia, undernutrition among primary school students is a serious issue. It is essential to implement nutrition education and school feeding programs, improve drinking water sources, and boost the community’s economy to alleviate the problems.

Patient attitudes, experiences, and satisfaction with healthcare and office visit utilization among Medicare beneficiaries with type 2 diabetes.

To examine patient attitudes, experiences, and satisfaction with healthcare associated with office visit utilization among Medicare beneficiaries with type 2 diabetes. We analyzed the 2019 Medicare Current Beneficiary Survey Public Use File of beneficiaries aged ≥65 years with type 2 diabetes (n = 1092). The ordinal dependent variable was defined as 0, 1 to 5, and ≥6 office visits. An ordinal partial proportional odds model was conducted to examine associations of beneficiaries' attitudes, experiences, and satisfaction with healthcare and office visit utilization. Among the beneficiaries, approximately 17.7%, 22.8%, and 59.5% reported having 0, 1 to 5, and ≥6 office visits, respectively. Being male (OR = 0.67, p = 0.004), Hispanic (OR = 0.53, p = 0.006), divorced/separated (OR = 0.62, p = 0.038) and living in a non-metro area (OR = 0.53, p < 0.001) were associated with a lower likelihood of attending more office visits. Trying to keep sickness to themselves (OR = 0.66, p = 0.002) and dissatisfaction with the ease and convenience of getting to providers from home (OR = 0.45, p = 0.010) were associated with a lower likelihood of having more office visits. The proportion of beneficiaries foregoing office visits is concerning. Attitudes concerning healthcare and transportation challenges can be barriers to office visits. Efforts to ensure timely and appropriate access to care should be prioritized for Medicare beneficiaries with diabetes.

Understanding Flex-Route Transit Adoption from a Stage of Change Perspective

Given the potential benefits of flex-route transit for the environment and traffic congestion, many cities have goals for diffusing flex-route transit. However, previous studies have focused on practical experience, strategic planning, and operational planning of flex-route transit. Few studies have identified the determinants of flex-route transit adoption. This study aims to address the effect of demographic characteristics and psychological factors on flex-route transit adoption by employing a stage of change framework. First, the transtheoretical model is applied to divide respondents into five ordered stages (i.e., Precontemplation, Contemplation, Preparation, Action, and Maintenance). Second, a survey was conducted in Beijing, China, using an online platform to obtain the demographic characteristics and measurement items of the respondents in the five ordered stages. Then, a structural equation model is applied to quantify psychological factors. In addition, the partial proportional odds (PPO) model is employed to estimate the best model and identify the determinants of flex-route transit adoption. Finally, an elasticity analysis is conducted to uncover the effect of determinants on flex-route transit adoption in the five ordered stages. The results suggest that the PPO model has the best fit and validity. The model reveals the significant implications of psychological factors and demographic characteristics for transport policy in various stages. These findings show that, regardless of the initial stage, interventions concentrating on psychological factors and demographic characteristics appear to have the potential to transfer the stage of individuals from one to another. To make policies as effective as possible for promoting flex-route transit adoption, the targeted interventions should be complemented in the specific stage.

Influential Factors of Household Car and Vehicle Ownership in Urban Areas of Turkey

Car and vehicle ownership levels in developing countries are gradually increasing, leading to traffic congestion, energy consumption, and air pollution. As a developing country, Turkey encounters many of the issues caused by this rapid increase in car ownership. This paper aims to examine potential determinants of household car and vehicle ownership behavior in urban areas of Turkey by concentrating on three cities (Ankara, Erzurum, and Bayburt) that are distinct in population, geographical region, and public transit services. For this purpose, a written survey was administered to 1389 households living in these cities. The data is analyzed using alternative ordered response models—the generalized ordered logit, partial proportional odds (PPO), and heteroskedastic ordered logit models. To the best of our knowledge, this study is the first attempt to compare alternative ordered response models to determine car and vehicle ownership behavior in Turkey. Consequently, the PPO model was found to be the most parsimonious model among the others. The results demonstrated that household car and vehicle ownership behavior in Turkey differs significantly with urban area size. The estimation results also revealed that several key drivers, including type of dwelling, parking availability, household monthly income, and public transit use, significantly influence Turkish households’ car and vehicle ownership levels. This study’s empirical findings may provide insight to policymakers and stakeholders for future transportation strategies and policies.

Identifying the Factors Contributing to Freeway Crash Severity Based on Discrete Choice Models

The freeway’s operation safety has attracted wide attention. In order to mitigate the losses brought on by traffic accidents on freeways, discrete choice models were constructed based on the statistical analysis method to quantitatively analyze the significance and magnitude of the impact of multiple dimensional factors on crash severity. Based on 1154 accidents that occurred on Zhejiang Province’s Hang-Jin-Qu Fressway from 2013 to 2018, the distribution characteristics of crash severity were analyzed. The dependent variable was the crash injury severity, which was categorized into property damage only (PDO), injury, and fatal. As independent variables, 15 candidate variables representing four aspects, including driver, vehicle, road, and environmental conditions, were chosen. Considering the ordered characteristics of the variables, the models developed included the ordered logit, the generalized ordered logit, and the partial proportional odds models. The Brant test found that the previous two models had difficulty dealing with the problem of partial variables that did not fit the parallel-lines assumption, and the conclusions were finally discussed through the partial proportional odds model results. The findings indicate that 11 factors have significant consequences. Five variables, namely “mountainous”, “female”, “driving experience 2- years”, “large vehicle responsible”, and “vehicle not going straight”, violated the parallel-lines assumption. Female drivers and drivers aged 55+ years were more likely to suffer injuries and fatalities in collisions with guardrails and other objects. Large vehicles being involved and vehicles not going straight enhanced the likelihood of injury and fatal outcomes when drivers had 2- years of experience. Wet-skid road conditions enhanced the likelihood of injury accidents, and driving at nighttime without lighting increased the likelihood of fatal accidents. Departments responsible for traffic management can take full account of these variations and develop focused proposals for improvement.

Analyzing dental fluorosis data using a novel Bayesian model for clustered longitudinal ordinal outcomes with an inflated category.

We propose a Bayesian hurdle mixed-effects model to analyze longitudinal ordinal data under a complex multilevel structure. This research was motivated by the dataset gathered from the Iowa Fluoride Study (IFS) in order to establish the relationships between fluorosis status and potential risk/protective factors. Dental fluorosis is characterized by spots on tooth enamel and is due to ingestion of excessive fluoride intake during enamel formation. Observations are collected from multiple surface zones on each tooth and on all available teeth of children from the studied cohort, which are longitudinally observed at ages 9, 13, and 17. The data not only exhibit a complex hierarchical structure, but also have a large proportion of zero values that are likely to follow different statistical patterns from non-zero categories. Therefore, we develop a hurdle model to consider the zero category separately, while a proportional odds model is used for the positive categories. The estimated parameters are obtained from a Gibbs sampler implemented by the OpenBUGS software. Our model is compared with two popular methods for ordinal data: the proportional odds model and the partial proportional odds model. We perform a comprehensive analysis of the IFS data and evaluate the accuracy and effectiveness of our methodology through simulation studies. Our discoveries provide novel insights to statisticians and dental practitioners about the associations between patient and clinical characteristics and dental fluorosis.

1161. Vaccination During Acute COVID-19 Infection Protects Against 30 Day Adverse Outcomes

Abstract Background Therapeutic vaccination following SARS-CoV-2 infection might stimulate anti-viral immunity and improve patient outcomes. We investigated, amongst previously unvaccinated patients, whether vaccination with the Pfizer, Moderna, or Johnson &amp; Johnson vaccines within 14 days of a positive SARS-CoV-2 test affected 30-day patient outcomes. Methods Using a deidentified national electronic health record dataset (Optum, Inc.), we identified previously unvaccinated patients who tested positive for COVID-19 between 12/11/2020 and 12/19/2021. Among this cohort, 1,909 patients received a first vaccine dose within 14 days (vaccinated) while 446,309 did not receive a first dose of vaccine within 30 days of their first positive test (unvaccinated). We performed 1:1 propensity score matching based on age, gender, race, ethnicity, region, BMI, insurance, and comorbidities from the Charlson Comorbidity Index. Next, we compared odds of severe outcomes within 30 days between vaccinated and unvaccinated groups using a partial proportional odds model with the following ordinal severity outcome: no hospitalization, hospitalization, ICU stay, or death (Stata version 17.0, α = 0.05). Results 1,909 vaccinated patients were propensity score-matched to 1,909 unvaccinated patients. The final matched cohort was statistically indistinguishable (p &amp;gt; 0.05) for all metrics used in propensity score calculation. This matched cohort (n = 3,818) was 58.6% female, 67.7% white, 12.6% Hispanic, and 56.4% commercially insured, with a mean age of 50.6 years and a similar comorbidity profile. A partial proportional odds model showed that unvaccinated patients were at increased risk for hospitalization and higher ordered outcomes (OR = 1.19, 95% CI: 1.02-1.39), ICU stay and higher ordered outcomes (OR 1.63, 95% CI: 1.21-2.20), and death (OR 4.57, 95% CI: 2.50-8.37). Conclusion Among previously unvaccinated patients, those who received a first dose vaccine within 14 days of a positive COVID-19 test were less likely to experience hospitalization, ICU stay, or death compared to matched peers who did not receive a first dose in the acute phase of infection. The sample size of patients vaccinated during the acute phase is limited, so further studies are indicated to evaluate the safety and efficacy of this practice. Disclosures Christoph U. Lehmann, MD, FAAP, FACMI, FIAHSI, Celanese: Stocks/Bonds|Markel: Stocks/Bonds|Springer: Honoraria.

Extreme Poverty Trap In Kalimantan Barat

Poverty is complex, conceptually and empirically, because it will affect how to understand poverty, its analysis, and policy formulation to overcome poverty. World Bank defines International Poverty Line (GK) as US$ 1.9 as it adjusts for inflation and living standards. Indonesia's poverty rate released by BPS uses a monetary approach, GK, which represents the minimum amount of money a person needs to meet food needs, equivalent to 2100 calories and other non-food needs. Ordinal regression Partial Proportional Odds Model (PPOM) found the best model with independent variables: Number of Household Members, Age, Defecation Facilities, Diplomas, Lightning, Main Activities, and Access to Clean Water, and all these variables significantly affect the status of poor both Extreme Poor, Poor, and Near Poor levels. It was found that Odds Ratio was very different at the Extreme Poor level. It was concluded that this category had different tendencies from other levels. Handling the extreme poor with various conditions requires different handling than the poor. Extremely poor with one household member, aged 1-14 years and 60 years and over, more in need of Social Assistance from the government. Extreme Poor with certain other conditions requires more research to determine the most effective alleviation program.

Nutritional status, alcohol-tobacco consumption behaviour and cognitive decline among older adults in India

Cognition capacity is essentially age-dependent and it is associated with the overall well-being of an individual. The public health aspects of cognitive research primarily focus on the possible delaying of cognitive decline among the older adult population. In this context, using the most recent round of the Longitudinal Ageing Study in India, 2017–2018 data, this study examines the cognition capacity among older adults aged 45 and above subject to their nutritional health and health behaviour (tobacco and alcohol consumption). It is observed that almost one in every tenth individual (10%) above 45 years of age in India shows low cognition scores. Low cognition is much more prevalent among 60 + females than males. Around one-fifth of the underweight older adults (18%) demonstrate low cognition capacity among them. Of those older adults who consume only tobacco, 11% of them demonstrate low cognition than the rest. The partial proportional odds model estimation shows that older adults are at higher risk of developing low cognition with increasing age and beyond age 65, the individuals carry a critically higher risk to experience low cognition. The estimation also shows that with increasing age older adults are higher likely to experience poor cognition independent of nutritional status, but underweight older adults are comparatively more likely to experience low cognition followed by normal and overweight older adults. In terms of alcohol-tobacco consumption behaviour, older adults who consume both are more likely to experience low cognition with increasing age followed by ‘only alcohol consumers’, and ‘only tobacco consumers’.

Partial proportional odds model for analyzing pedestrian crashes, threshold heterogeneity by scale and proportional odds factor

Despite low traffic in Wyoming, pedestrian crash severity accounts for a high number of fatalities in the state. Thus this study was conducted to highlights factors contributing to those crashes. The results highlighted that drivers under influence, type of vehicle, location of crashes, estimated speed of vehicles, driving over the recommended speed are some of factors contributing to the severity of crashes. In this study, we used proportional odds model which assumes that the impact of each attribute is consistent or proportional across various threshold values. However, it has been argued that this assumption might be unrealistic, especially at the presence of extreme values. Thus, the assumption was relaxed in this study by shifting the thresholds based on some explanatory attributes, or proportional odds effects. In addition, we accounted for the spread rate, or scale, of the model's latent distribution of pedestrian crashes. The results highlighted that the partial proportional odds model through proportional odds factor and scale effects result in a significant improvement in model fit compared with the standard proportional odds model. Comparisons were also made across standard normal, simple partial ordinal model, and partial ordinal accounting for scale heterogeneity. In addition, various potential threshold structures such as symmetric and flexible were considered, but similar goodness of fits were observed across all those models. Extensive discussion has been made regarding the formulation of the implemented methodology, and its implications. • More flexibility is given to the model by relaxing the assumption of proportional odds and scale, or spread rate. • The results highlight a significant improvement in the model fit, compared with the standard model. • Some of factors contributing to the severity of pedestrian crashes are discussed. • Almost all identified results linked to the lack of attention and caution of the drivers.

Modeling injury severity of crashes involving trucks: Capturing and exploring risk factors associated with land use and demographic in addition to crash, driver, and on-network characteristics

Nearly 499,000 motor vehicle crashes involving trucks were reported across the United States in 2018, out of which 22% resulted in fatalities and injuries. Given the growing economy and demand for trucking in the future, it is crucial to identify the risk factors to understand where and why the likelihood of getting involved in a severe or moderate injury crash with a truck is higher. The focus of this research, therefore, is on developing a methodology, capturing and integrating data, exploring, and identifying risk factors associated with surrounding land use and demographic characteristics in addition to crash, driver, and on-network characteristics by modeling injury severity of crashes involving trucks. Crash data for Mecklenburg County in North Carolina from 2013 to 2017 was used to develop partial proportional odds model and identify risk factors influencing injury severity of crashes involving trucks. The findings indicate that dark lighting condition, inclement weather condition, the presence of double yellow or no-passing zone, road sections with speed limit >40 mph and curves, and driver fatigue, impairment, and inattention have a significant influence on injury severity of crashes involving trucks. These outcomes indicate the need for effective geometric design and improved visibility to reduce the injury severity of crashes involving trucks. The likelihood of a severe or moderate injury crash involving a truck is also high in areas with high employment, government, light commercial, and light industrial land uses. The findings can be used to identify potential risk areas, proactively plan and prioritize the allocation of resources to improve safety of transportation system users in these areas.

Exploring the heterogeneous effects of zonal factors on bicycle injury severity: latent class clustering analysis and partial proportional odds models

Despite the benefits of cycling being widely accepted, bicycle safety—especially severe injury—has received increasing attention due to the vulnerability of bicyclists on the road. Factors contributing to varying bicycle injury severity have been identified in the literature. For the zonal factors, variables related to sociodemographic and household characteristics, built environments, land use, and traffic conditions are considered. However, it is rare that the heterogeneity and hierarchal features of bicycle injury severity are simultaneously considered. This study contributes to the literature by investigating the heterogeneous effects of zonal factors on varying bicycle injury severity, using a 3-year crash data set from the Lower Layer Super Output Areas of London. A combination of latent class clustering and partial proportional odds methods was developed. First, five subgroups of bicycle crashes were identified based on the latent class clustering method. Afterward, partial proportional models were developed separately for different clusters. Results indicate that a series of factors is found to be associated with the occurrence of severe bicycle injuries. However, effects of these factors could be distinctive among different clusters. For example, some factors only have significant impacts in the specific crash clusters. Furthermore, heterogeneous effects of the same factors in one or different clusters are discovered. The findings of this study can be helpful for the development of cycle infrastructures, traffic management, and safety education that can enhance the risk perception of bicyclists and reduce the occurrence of severe bicycle injuries.

Multimorbidity and health-related quality of life among patients attending chronic outpatient medical care in Bahir Dar, Northwest Ethiopia: The application of partial proportional odds model.

Multimorbidity, the presence of two or more chronic non-communicable diseases (NCDs) in a given person affects all aspects of people's lives. Poor quality of life (QoL) is one of the major consequences of living with multimorbidity. Although healthcare should support multimorbid individuals to achieve a better quality of life, little is known about the effect of multimorbidity on the QoL of patients living with chronic conditions. This study aimed to determine the influence of multimorbidity on QoL among clients attending chronic outpatient medical care in Bahir Dar, Northwest Ethiopia. A multi-centered facility-based study was conducted among 1440 participants aged 40+ years. Two complementary methods were employed to collect sociodemographic and disease related data. We used the short form (SF-12 V2) instrument to measure quality of life (QoL). The data were analyzed by STATA V.16, and a multivariate partial proportional odds model was fitted to identify covariates associated with quality of life. Statistical significance was considered at p-value <0.05. Multimorbidity was identified in 54.8% (95% CI = 52.2%-57.4%) of the sample. A significant proportion (33.5%) of the study participants had poor QoL and a quarter (25.8%) of them had moderate QoL. Advanced age, obesity and living with multimorbidity were the factors associated with poor QoL. Conversely, perceived social support and satisfaction with care were the variables positively associated with better QoL. The magnitude of multimorbidity in this study was high and individuals living with multimorbidity had a relatively poorer QoL than those without multimorbidity. Care of people with chronic multiple conditions has to be oriented to the realities of multimorbidity burden and its implication on QoL. It is also imperative to replicate the methods we employed to measure and analyze QoL data in this study for facilitating comparison and further development of the approaches.

Antimicrobials in dog-to-dog bite wounds: A retrospective study of 1526 dog bite events (1999-2019).

Although dog-to-dog bite wounds (DBW) are common, few studies worldwide have evaluated antimicrobial usage patterns or appropriateness of use. Report frequency and results of DBW cultures, including antimicrobial susceptibility patterns. Determine the most commonly prescribed antimicrobials and their appropriateness for the treatment of DBW, and if antimicrobial importance is associated with wound severity, clinic type or year. One thousand five hundred twenty-six dog bite events involving 1436 dogs presenting with DBW from 3 Australian university clinics from 1999 to 2019. Retrospective study. Medical records were reviewed for presenting signs, culture and susceptibility testing, antimicrobial treatment, and outcome. A partial proportional odds model was used to determine if use of higher importance antimicrobials was associated with wound severity, clinic, or year. Antimicrobials were prescribed in 88.1% (1344/1526) of DBW. Amoxicillin-clavulanic acid was prescribed in 73.4% (1121/1526) of dogs, followed by first-generation cephalosporins, 18.1% (277/1526). Of a total of 1647 antimicrobial prescriptions, underdosing occurred in 13.4% for AMC (220/1647) and 26.1% (81/310) of dogs prescribed first generation cephalosporins. There was an association between the increased use of high-importance antimicrobials and wound severity (P < .001), antimicrobial polytherapy (P < .001) and year (P < .001). The odds of the clinic with specialists prescribing high-importance antimicrobials compared to those of medium importance for DBW was 82% less than that of a semi-rural, mixed and general practice. Culture and susceptibility (C&S) testing was performed in 1.8% of dogs. Empirical use of amoxicillin-clavulanic acid was common for DBW. Increasing wound severity was associated with greater use of high-importance antimicrobials. While C&S testing was rarely performed, routine susceptibility profiles are recommended to optimize antimicrobial stewardship.

Determinants of Immunization Status Among 12-24 Months Old Children in Ethiopia: Using 2019 Ethiopian Mini Demographic and Health Survey Data

Background: Vaccination is a global success story, one of the most effective and successful health interventions for health and development, saving the lives of millions of children every year. In 2018, nearly 870,000 Ethiopian children did not receive the life-saving measles, diphtheria, and tetanus vaccines. This study aimed to determine what factors influence children's immunization status in Ethiopia. Methods: Immunization status was examined in a sample of 1843 children aged 12-24 months using data from the 2019 Ethiopian Mini Demographic and Health Survey 2019. Percentages were used to show the prevalence of immunization status among children. The marginal likelihood effect was used to determine the impact of each category of the explanatory variable on one response category of immunization status. Ordinal logistic regression models were constructed, and the best-fitting model was selected to identify significant immunization status variables. Results: The prevalence of immunization status among children was found to be 72.2% (34.2% fully immunized and 38.0% partially immunized), while about 27.8% of children were non-immunized. The fitted partial proportional odds model revealed that child immunization status was significantly associated with region afar (OR = 7.90; CI: 4.78-11.92), family planning use (OR = 0.69; CI: 0.54-0.88), residence (OR = 2.22;CI: 1.60-3.09), antenatal visit (OR = 0.73;CI: 0.53-0.99), and delivery place (OR = 0.65;CI: 0.50-0.84). Conclusions: Vaccinating children was a significant step forward in improving and protecting child health in Ethiopia. The study showed that the prevalence of non-immunized children varied between rural (33.6%) and uneducated mothers (36.6%). As a result, it is agreeable that treatments are better to focus on targeting essential childhood vaccinations by promoting maternal education, antenatal visits, and maternal access to health care.

Bayesian discrete conditional transformation models

We propose a novel Bayesian model framework for discrete ordinal and count data based on conditional transformations of the responses. The conditional transformation function is estimated from the data in conjunction with an a priori chosen reference distribution. For count responses, the resulting transformation model is novel in the sense that it is a Bayesian fully parametric yet distribution-free approach that can additionally account for excess zeros with additive transformation function specifications. For ordinal categoric responses, our cumulative link transformation model allows the inclusion of linear and non-linear covariate effects that can additionally be made category-specific, resulting in (non-)proportional odds or hazards models and more, depending on the choice of the reference distribution. Inference is conducted by a generic modular Markov chain Monte Carlo algorithm where multivariate Gaussian priors enforce specific properties such as smoothness on the functional effects. To illustrate the versatility of Bayesian discrete conditional transformation models, applications to counts of patent citations in the presence of excess zeros and on treating forest health categories in a discrete partial proportional odds model are presented.

Disparities in Online Use Behaviours and Chinese Digital Inclusion: A 10-Year Comparison.

This study focuses on the disparities in Chinese online use behaviours (frequency and diversity) based on educational background and socioeconomic status over 10 years to reveal the Chinese digital inclusion process. We used the China Family Panel Studies (CFPS) 2010 and 2018 panels and considered the time and cohort effects separately. Ordinary least squares analysis revealed usage frequency. The generalized partial proportional odds model demonstrated participants’ prioritization of online study, work, entertainment, and social activity. The results show that the profile of the individuals with the most time spent online has changed from those with high education and income levels to mid-range education and income levels. Individuals with high education and income levels prefer to use the internet for studying and working. There are no clear preference differences between entertainment and social activities amongst most educational backgrounds and socioeconomic statuses. Regarding frequency of internet use, digital inclusion has spread downwards from the upper to the middle classes. Regarding diverse internet uses, upper-class individuals prefer to conduct capital-enhancing activities, and youth remain the main force for diverse online activities; however, over time, middle-aged groups have increased their capital-enhancing activities, and older adults have increased their digital social activities.

Reducing the gap in nonvisitor studies: Evidence on museum attendance from the German National Educational Panel Study

Looking at museums as informal learning environments, it is clear that detailed information on visitors and especially on nonvisitors is key to preparing adequate offers. However, representative or population-based audience studies are scarce, and even less information is available on nonvisitors. Based on a representatively drawn German adult cohort (analytic sample: n = 6,837), we look at characteristics of museum audiences and use partial proportional odds models to describe factors that characterize both visitors and nonvisitors. Results show strong evidence for relevant factors outside the realm of demographic and socioeconomic variables, and that it is especially cultural capital and cultural participation that explain museum visits. We conclude by arguing in favor of developing broader models to conceptualize museum attendance and especially nonattendance.

Investigating the Risk Factors Associated with Injury Severity in Pedestrian Crashes in Santiago, Chile.

Pedestrians are vulnerable road users that are directly exposed to road traffic crashes with high odds of resulting in serious injuries and fatalities. Therefore, there is a critical need to identify the risk factors associated with injury severity in pedestrian crashes to promote safe and friendly walking environments for pedestrians. This study investigates the risk factors related to pedestrian, crash, and built environment characteristics that contribute to different injury severity levels in pedestrian crashes in Santiago, Chile from a spatial and statistical perspective. First, a GIS kernel density technique was used to identify spatial clusters with high concentrations of pedestrian crash fatalities and severe injuries. Subsequently, partial proportional odds models were developed using the crash dataset for the whole city and the identified spatial clusters to examine and compare the risk factors that significantly affect pedestrian crash injury severity. The model results reveal higher increases in the fatality probability within the spatial clusters for statistically significant contributing factors related to drunk driving, traffic signage disobedience, and imprudence of the pedestrian. The findings may be utilized in the development and implementation of effective public policies and preventive measures to help improve pedestrian safety in Santiago.