Hierarchical Regression Approach Research Articles

Is harmony still in the local socialist officials’ hearts

Purpose The purpose of this paper is to assess if the core value of Chinese traditional culture (harmony) still remains in managers’ hearts, and what factors influence this core value’s persistence. This was done by assessing the harmonious competencies of China’s county and department-level officials based on the competing values framework. Design/methodology/approach A survey of 1,000 county and department-level officials was taken at random based on the Ministry of Human Resources and Social Security’s public sector employee listings. An empirical assessment was made and a hierarchical linear regression approach was used. Findings Though Chinese traditional culture has been blended with communist ideology and Western practices in government administration, the core value of Chinese bureaucracy still remains that which is carried in officials’ minds. In general, public officials possess a satisfactory level of harmonious competency. The regression results showed that some factors influence harmonious competency significantly, which disproves the view that harmonious competency might be merely engendered in officials by being born and growing up in Chinese traditional culture. Originality/value Given the assumption that a Chinese-born citizen could inherit the core value of its traditional culture is commonplace, the paper reveals that because the current Chinese culture is a mix of socialist thinking, traditional culture and Western practices, it cannot be assumed any more that the core value of Chinese culture is inherited automatically. On the contrary, it could be promoted by changing or cultivating certain factors in workplaces.

Abstract P6-09-08: Exposure to multiple sources of polycyclic aromatic hydrocarbon and breast cancer incidence

Abstract Background. Previous epidemiologic studies, including our own, have consistently linked long-term exposure to single-source polycyclic aromatic hydrocarbons (PAHs) to increased breast cancer incidence. It is unclear whether single sources, specific groups, or all PAH sources should be targeted for breast cancer risk reduction. This study considers the impact on breast cancer incidence from multiple PAH exposure sources in a single model, which better reflects exposure to these complex mixtures. Methods. In a population-based case-control study conducted on Long Island, New York (N=1,508 breast cancer cases/1,556 controls), a Bayesian hierarchical regression approach was used to estimate adjusted posterior means and credible intervals (CrI) for the adjusted odds ratios (ORs) for PAH exposure sources, considered singly and as groups: active smoking; residential environmental tobacco smoke (ETS); indoor and outdoor air pollution; and grilled/smoked meat intake. Results. Most women were exposed to PAHs from multiple sources. In a hierarchical model, breast cancer incidence was positively associated with ETS from a spouse (OR=1.20, 95%CrI=1.03, 1.42) and residential synthetic firelog burning (OR=1.30, 95%CrI=1.06, 1.60). Additionally, PAH exposure groups, including ingestion (OR=1.45, 95%CrI=1.16, 1.79), indoor stove/fireplace use (OR=1.30, 95%CrI=1.02, 1.62), and total indoor sources (active smoking, ETS from spouse, grilled/smoked meat intake, stove/fireplace use, OR=1.46, 95%CrI=1.03, 2.05), were associated with increased breast cancer incidence. Conclusions. Groups of PAH sources, especially those for ingestion and indoor sources, were associated with a 30-50% increase in breast cancer incidence. PAH exposure is ubiquitous and a potentially modifiable breast cancer risk factor. Citation Format: White AJ, Bradshaw PT, Herring AH, Teitelbaum SL, Beyea J, Stellman SD, Steck SE, Mordukhovich I, Eng SM, Engel LS, Conway K, Hatch M, Neugut AI, Santella RM, Gammon MD. Exposure to multiple sources of polycyclic aromatic hydrocarbon and breast cancer incidence. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P6-09-08.

Exposure to multiple sources of polycyclic aromatic hydrocarbons and breast cancer incidence

BackgroundDespite studies having consistently linked exposure to single-source polycyclic aromatic hydrocarbons (PAHs) to breast cancer, it is unclear whether single sources or specific groups of PAH sources should be targeted for breast cancer risk reduction. ObjectivesThis study considers the impact on breast cancer incidence from multiple PAH exposure sources in a single model, which better reflects exposure to these complex mixtures. MethodsIn a population-based case-control study conducted on Long Island, New York (N=1508 breast cancer cases/1556 controls), a Bayesian hierarchical regression approach was used to estimate adjusted posterior means and credible intervals (CrI) for the adjusted odds ratios (ORs) for PAH exposure sources, considered singly and as groups: active smoking; residential environmental tobacco smoke (ETS); indoor and outdoor air pollution; and grilled/smoked meat intake. ResultsMost women were exposed to PAHs from multiple sources, and the most common included active/passive smoking and grilled/smoked food intake. In multiple-PAH source models, breast cancer incidence was associated with residential ETS from a spouse (OR=1.20, 95%CrI=1.03, 1.40) and synthetic firelog burning (OR=1.29, 95%CrI=1.06, 1.57); these estimates are similar, but slightly attenuated, to those from single-source models. Additionally when we considered PAH exposure groups, the most pronounced significant associations included total indoor sources (active smoking, ETS from spouse, grilled/smoked meat intake, stove/fireplace use, OR=1.45, 95%CrI=1.02, 2.04). ConclusionsGroups of PAH sources, particularly indoor sources, were associated with a 30–50% increase in breast cancer incidence. PAH exposure is ubiquitous and a potentially modifiable breast cancer risk factor.

E. multilocularis infection in animals

E. multilocularis infection in animals

A Hierarchical Regression Approach for Unconstrained Face Analysis

Head pose and facial feature detection are important for face analysis. However, many studies reported good results in constrained environment, the performance could be decreased due to the high variations in facial appearance, poses, illumination, occlusion, expression and make-up. In this paper, we propose a hierarchical regression approach, Dirichlet-tree enhanced random forests (D-RF) for face analysis in unconstrained environment. D-RF introduces Dirichlet-tree probabilistic model into regression RF framework in the hierarchical way to achieve the efficiency and robustness. To eliminate noise influence of unconstrained environment, facial patches extracted from face area are classified as positive or negative facial patches, only positive facial patches are used for face analysis. The proposed hierarchical D-RF works in two iterative procedures. First, coarse head pose is estimated to constrain the facial features detection, then the head pose is updated based on the estimated facial features. Second, the facial feature localization is refined based on the updated head pose. In order to further improve the efficiency and robustness, multiple probabilitic models are learned in leaves of the D-RF, i.e. the patch’s classification, the head pose probabilities, the locations of facial points and face deformation models (FDM). Moreover, our algorithm takes a composite weight voting method, where each patch extracted from the image can directly cast a vote for the head pose or each of the facial features. Extensive experiments have been done with different publicly available databases. The experimental results demonstrate that the proposed approach is robust and efficient for head pose and facial feature detection.

How users adopt healthcare information: An empirical study of an online Q&A community

ObjectivesThe emergence of social media technology has led to the creation of many online healthcare communities, where patients can easily share and look for healthcare-related information from peers who have experienced a similar problem. However, with increased user-generated content, there is a need to constantly analyse which content should be trusted as one sifts through enormous amounts of healthcare information. This study aims to explore patients’ healthcare information seeking behavior in online communities. MethodsBased on dual-process theory and the knowledge adoption model, we proposed a healthcare information adoption model for online communities. This model highlights that information quality, emotional support, and source credibility are antecedent variables of adoption likelihood of healthcare information, and competition among repliers and involvement of recipients moderate the relationship between the antecedent variables and adoption likelihood. Empirical data were collected from the healthcare module of China’s biggest Q&A community—Baidu Knows. Text mining techniques were adopted to calculate the information quality and emotional support contained in each reply text. A binary logistics regression model and hierarchical regression approach were employed to test the proposed conceptual model. ResultsInformation quality, emotional support, and source credibility have significant and positive impact on healthcare information adoption likelihood, and among these factors, information quality has the biggest impact on a patient’s adoption decision. In addition, competition among repliers and involvement of recipients were tested as moderating effects between these antecedent factors and the adoption likelihood. Results indicate competition among repliers positively moderates the relationship between source credibility and adoption likelihood, and recipients’ involvement positively moderates the relationship between information quality, source credibility, and adoption decision. ConclusionsIn addition to information quality and source credibility, emotional support has significant positive impact on individuals’ healthcare information adoption decisions. Moreover, the relationships between information quality, source credibility, emotional support, and adoption decision are moderated by competition among repliers and involvement of recipients.

The socio-economic determinants of infant mortality in Nepal: analysis of Nepal Demographic Health Survey, 2011.

BackgroundInfant mortality reflects not only the health of infants but societal well-being as a whole. This study explores distal socioeconomic and related proximate determinants of infant mortality and provides evidence for designing targeted interventions.MethodsSurvival information on 5391 live born infants (2006–2010) was examined from the nationally representative Nepal Demographic Health Survey 2011. Bivariate logistic regression and multivariate hierarchical logistic regression approaches were performed to analyze the distal-socioeconomic and related proximate determinants of infant mortality.ResultsSocio-economic distal determinants are important predictors for infant mortality. For example, in reference to infants of the richest class, the adjusted odds ratio of infant mortality was 1.66 (95 % CI: 1.00–2.74) in middle class and 1.87 (95 % CI: 1.14–3.08) in poorer class, respectively. Similarly, the populations of the Mountain ecological region had a higher odds ratio (aOR =1.39, 95 % CI: 0.90–2.16) of experiencing infant mortality compared with the populations of the Terai plain region. Likewise, the population of Far-western development region had a higher adjusted odds ratio (aOR =1.62, 95 % CI: 1.02–2.57) of experiencing infant mortality than the Western development region. Moreover, the association of proximate determinants with infant mortality was statistically significant. For example, in reference to size at birth, adjusted odds ratio of infant dying was higher for infants whose birth size, as reported by mothers, was very small (aOR = 3.41, 95 % CI: 2.16–5.38) than whose birth size was average. Similarly, fourth or higher birth rank infants with a short preceding birth interval (less than or equal to 2 years) were at greater risk of dying (aOR =1.74, 95 % CI: 1.16–2.62) compared to the second or third rank infants with longer birth intervals. A short birth interval of the second or the third rank infants also increased the odds of infant death (aOR = 2.03, 95 % CI: 1.23–3.35).ConclusionsSocioeconomic distal and proximate determinants are associated with infant mortality in Nepal. Infant mortality was higher in the poor and middle classes than the wealthier classes. Population of Mountain ecological region and Far western development region had high risk of infant mortality. Similarly, infant dying was higher for infants whose birth size, as reported by mothers, was very small and who has higher birth rank and short preceding birth interval. This study uniquely addresses both broader socioeconomic distal and proximate determinants side by side at the individual, household and community levels. For this, both comprehensive, long-term, equity-based public health interventions and immediate infant care programs are recommended.

An examination of disparities in cancer incidence in Texas using Bayesian random coefficient models.

Disparities in cancer risk exist between ethnic groups in the United States. These disparities often result from differential access to healthcare, differences in socioeconomic status and differential exposure to carcinogens. This study uses cancer incidence data from the population based Texas Cancer Registry to investigate the disparities in digestive and respiratory cancers from 2000 to 2008. A Bayesian hierarchical regression approach is used. All models are fit using the INLA method of Bayesian model estimation. Specifically, a spatially varying coefficient model of the disparity between Hispanic and Non-Hispanic incidence is used. Results suggest that a spatio-temporal heterogeneity model best accounts for the observed Hispanic disparity in cancer risk. Overall, there is a significant disadvantage for the Hispanic population of Texas with respect to both of these cancers, and this disparity varies significantly over space. The greatest disparities between Hispanics and Non-Hispanics in digestive and respiratory cancers occur in eastern Texas, with patterns emerging as early as 2000 and continuing until 2008.

Hierarchical regression for analyses of multiple outcomes.

In cohort mortality studies, there often is interest in associations between an exposure of primary interest and mortality due to a range of different causes. A standard approach to such analyses involves fitting a separate regression model for each type of outcome. However, the statistical precision of some estimated associations may be poor because of sparse data. In this paper, we describe a hierarchical regression model for estimation of parameters describing outcome-specific relative rate functions and associated credible intervals. The proposed model uses background stratification to provide flexible control for the outcome-specific associations of potential confounders, and it employs a hierarchical "shrinkage" approach to stabilize estimates of an exposure's associations with mortality due to different causes of death. The approach is illustrated in analyses of cancer mortality in 2 cohorts: a cohort of dioxin-exposed US chemical workers and a cohort of radiation-exposed Japanese atomic bomb survivors. Compared with standard regression estimates of associations, hierarchical regression yielded estimates with improved precision that tended to have less extreme values. The hierarchical regression approach also allowed the fitting of models with effect-measure modification. The proposed hierarchical approach can yield estimates of association that are more precise than conventional estimates when one wishes to estimate associations with multiple outcomes.

Students’ Perceptions of Person–Environment Fit

This study examines the validity of the three-factor model of person–environment (P-E) fit perceptions in a sample of German university students ( N = 326) and examines the connection between these fit types, the Big Five personality traits, and markers of academic success, namely, academic satisfaction, academic performance, and major change intention. Building upon previous research, a three-factor model of P-E fit perceptions with complex loadings was hypothesized differentiating between interest-major (I-M) fit, needs-supplies (N-S) fit, and demands-abilities (D-A) fit. Results from confirmatory factor analyses supported the suggested three-factor solution. Zero-order correlations, multiple regression analyses, and relative weight analyses identified perceived I-M fit as the key predictor of academic satisfaction and major change intention. D-A fit was the strongest predictor of academic performance. Finally, a hierarchical regression approach revealed that personality traits did not improve the prediction of any outcome over perceived P-E fit.

Predictive statistical models linking antecedent meteorological conditions and waterway bacterial contamination in urban waterways

Although the relationships between meteorological conditions and waterway bacterial contamination are being better understood, statistical models capable of fully leveraging these links have not been developed for highly urbanized settings. We present a hierarchical Bayesian regression model for predicting transient fecal indicator bacteria contamination episodes in urban waterways. Canals, creeks, and rivers of the New York City harbor system are used to examine the model. The model configuration facilitates the hierarchical structure of the underlying system with weekly observations nested within sampling sites, which in turn were nested inside of the harbor network. Models are compared using cross-validation and a variety of Bayesian and classical model fit statistics. The uncertainty of predicted enterococci concentration values is reflected by sampling from the posterior predictive distribution. Issuing predictions with the uncertainty reasonably reflected allows a water manager or a monitoring agency to issue warnings that better reflect the underlying risk of exposure. A model using only antecedent meteorological conditions is shown to correctly classify safe and unsafe levels of enterococci with good accuracy. The hierarchical Bayesian regression approach is most valuable where transient fecal indicator bacteria contamination is problematic and drainage network data are scarce.

Export relational governance and control mechanisms

Purpose– The purpose of this paper is to examine the direct and interaction effects of relational governance and two control mechanisms, output control and process control in the context of international exchange relationships. Cross-border exchange relationships receive growing attention in the literature. Yet extant research has mainly examined single governance mechanisms. Among the few studies that investigate the interaction effects of relational governance and control mechanisms, some believe that the two mechanisms have conflicting effects, whereas others argue that they are complementary in nature.Design/methodology/approach– Based on a sample of 184 Chinese export ventures, the empirical paper adopts the hierarchical moderated multiple regression approach.Findings– The authors find that relational governance contributes positively to export performance, while output control leads negatively to export performance. The findings further suggest that output control complements relational governance to enhance export performance when combined. However, process control and relational governance substitute each other and reduce effectiveness when used simultaneously.Research limitations/implications– The study sheds new light on the ongoing debate about whether control mechanisms substitute or complement relational governance.Originality/value– The study is novel in addressing the issue of how relational governance interacts differently with two control mechanisms in the international exchange relationships.

Factors associated with health-promoting behavior of people with or at high risk of metabolic syndrome: Based on the health belief model

PurposeThe purpose of this study is to identify the associations between self-efficacy and the various factors in the Health Belief Model (HBM), and the health-promoting behaviors of people with, or at high risk of, Metabolic Syndrome (MS). Methods132 adults with two or more MS components were included in this cross-sectional study. Health-promoting behavior, self-efficacy and the four-constructs of HBM (perceived threat, cues, benefits, and barriers) were measured using validated tools. The contributions of each HBM factor towards the respective behavior were identified using a three-step hierarchical regression approach. ResultsAfter controlling for age, gender, education level, income and knowledge of MS, HBM factors accounted for 11% of the total variance in health-promoting behaviors. Beliefs about barriers were found to be a significant predictor of exercise (β=−.28, p<.01) and diet management (β=−.24, p=<.01), suggesting that a higher level of perceived barrier was associated with a lower frequency of health-promoting behaviors. In the final model, self-efficacy explained an additional 31% of the variance in exercise behavior and 13% in diet management behavior. ConclusionsSelf-efficacy and perceived barriers made independent contributions to health-promoting behavior among people with, or at high risk of, MS. Community health program targeting this particular group should tailor strategies that can enhance individuals’ self-efficacy and address barriers perceived.

Hierarchical facial landmark localization via cascaded random binary patterns

The main challenge of facial landmark localization in real-world application is that the large changes of head pose and facial expressions cause substantial image appearance variations. To avoid high dimensional facial shape regression, we propose a hierarchical pose regression approach, estimating the head rotation, face components, and facial landmarks hierarchically. The regression process works in a unified cascaded fern framework with binary patterns. We present generalized gradient boosted ferns (GBFs) for the regression framework, which give better performance than ferns. The framework also achieves real time performance. We verify our method on the latest benchmark datasets and show that it achieves the state-of-the-art performance.

The Moderating Effect of Environmental Turbulence in the Relationship between Entrepreneurial Management and Firm Performance

Contingency theory points out the adaptive management is crucial point to sustainable firm performance. This research aims to determine the relative importance of a set of variables comprising the four entrepreneurial management variables, i.e. strategic orientation, organization culture, organization structure, and reward system, and a set of environmental turbulence variables in predicting firm performance. This research uses firm-level data with observed population of this research is SMEs in Surabaya, Indonesia. Through adopting hierarchical regression approach and partial least square method, this study indicates that moderating effect of environmental turbulence changes the direction of relationship between entrepreneurial management and firm performance. During low environmental turbulence, entrepreneurial management has positive impact on firm performance, but the direction changes. Entrepreneurial management has negative impact on firm performance during high environmental turbulence.

Examining the relationship between branding and customers’ attitudes toward banking services

Purpose– This study aims to integrate consumer-based brand equity for a tourism destination (CBBETD) and the theory of planned behavior (TPB) to examine the relationship between branding and customers’ attitudes toward banking services.Design/methodology/approach– A ten-minute pen and paper questionnaire was distributed to customers of Iran’s Melli Bank in Isfahan as the biggest national bank in Iran through a multistage cluster-sampling approach. Data were collected from 364 customers and analyzed by hierarchical regression approach.Findings– Branding constructs including brand image, brand awareness, perceived quality and brand loyalty have a significant relationship with attitude constructs including affective attitude, subjective norm, perceived behavioral control and behavioral intention.Originality/value– This paper provides a practical framework derived from the CBBETD model and applies it in the context of banking services. The role and impact of its dimensions on customers’ attitudes has been demonstrated.

Strategic orientation and new product performance: The roles of technological capability

AbstractAlthough prior research has examined the linkage between strategic orientation and new product performance, existing empirical evidence suggests exploration of the effects of a firm's internal factors on this linkage is required. This study aims to fill the marketing literature gap by addressing how technological capability moderates the strategic orientation‐new product performance relationship. This study measures new product performance as a two‐dimensional construct to avoid the oversimplified bias. Research hypotheses are tested using a sample of 121 information system product projects and a hierarchical regression approach is utilized. Results show that (a) technological capability strengthens the market orientation‐performance relationship and (b) technological capability affects the financial performance effects of market and technology orientations via market performance. Copyright © 2014 ASAC. Published by John Wiley &amp; Sons, Ltd.

Emotional Exhaustion in Graduate Students: The Role of Engagement, Self-Efficacy and Social Support

Graduate students, particularly those based in research intensive universities are susceptible to exhaustion. Thestudy utilized a quantitative approach to test the impact of student engagement, self- efficacy, and social supporton college students’ emotional exhaustion. A hierarchical regression approach was used for analysis. Findingsdemonstrated that students who were engaged, and self –efficacious were less exhausted from their studies.Social support especially from advisors was important in helping students cope with emotional exhaustion.Additionally, student engagement proved to be important as it partially mediates the advisor support- exhaustionrelationship while fully mediating the self-efficacy- exhaustion relationship. Implications and suggestions forinstitutions of higher learning regarding intervention strategies to mitigate the exhaustion and burnout processwere discussed.

Effects of ambient air pollution on the prevalence of pneumonia in children: Implication for National Ambient Air Quality Standards in China

Pneumonia is the most important cause of child death in the world today. Recent findings suggest that exposure to outdoor air pollutants may increase the pneumonia occurrence, but so far the associations have not been clearly illustrated. Therefore, the effects of outdoor air pollutants and the episode day on childhood pneumonia were investigated by this study. A standardized questionnaire on health, home and environmental factors of 4988 children was conducted in the city of Changsha, China. Average exposure to ambient air pollutants during 2008–2011 was monitored by the air pollution monitoring stations of Changsha Environmental Protection Agency. A two-stage hierarchical regression approach was adopted to estimate the effects of PM10, SO2 and NO2 on pneumonia risk. The prevalence of pneumonia in children aged 3–6 years was 38.2%, which is greatly higher than the developed countries but lower than some developing countries. Furthermore, the increased risk of childhood pneumonia was significantly associated with elevated NO2 concentration (odds ratio (OR) = 1.157, 95% confidence interval (CI): 1.121–1.195) and the episode day (OR = 1.038, 95% CI: 1.024–1.051), but not significantly associated with PM10 and SO2. Exposure to traffic-related air pollution could play an important role in the development of pneumonia in preschool children. The revised National Ambient Air Quality Standards (2012) for NO2 has provided a better control strategy for ambient air quality to reduce the risk of adverse health effects such as pneumonia for children.

The effect of end user computing competence on human resource job performance: Mapping for human resource roles

The purpose of this paper is to explore the relationship between end user computing competence and job performance by different human resource (HR) roles. A research model was formulated based on two theories from both the technology-to-performance chain (TPC) model and the HR five role model. The study used a multiple hierarchical regression approach, in which 122 HR professionals within eight financial companies participated. The study found that end user computing competence positively influenced the job performance of the HR professionals, whereas the net explanatory power and the impacted end user computing competency factors varied across HR roles. These findings contribute to research related to end user computing competence and an expanded understanding of the factors that improve an HR professional’s job performance by different HR roles. The theoretical and managerial implications of these findings are discussed. Key words: End user computing competence, human resource (HR) roles, job performance, human resource competence.