Prediction in Multilevel Logistic Regression

The purpose of this article is to present a new method to predict the response variable of an observation in a new cluster for a multilevel logistic regression. The central idea is based on the empirical best estimator for the random effect. Two estimation methods for multilevel model are compared: penalized quasi-likelihood and Gauss-Hermite quadrature. The performance measures for the prediction of the probability for a new cluster observation of the multilevel logistic model in comparison with the usual logistic model are examined through simulations and an application.

ON MARGINALIZED MULTILEVEL MODELS AND THEIR COMPUTATION

Clustered data analysis is characterized by the need to describe both systematic variation in a mean model and cluster-dependent random variation in an association model. Marginalized multilevel models embrace the robustness and interpretations of a marginal mean model, while retaining the likelihood inference capabilities and flexible dependence structures of a conditional association model. Although there has been increasing recognition of the attractiveness of marginalized multilevel models, there has been a gap in their practical application arising from a lack of readily available estimation procedures. We extend the marginalized multilevel model to allow for nonlinear functions in both the mean and association aspects. We then formulate marginal models through conditional specifications to facilitate estimation with mixed model computational solutions already in place. We illustrate this approach on a cerebrovascular deficiency crossover trial.

Single nucleotide polymorphisms (SNPs) associated with TGF-beta pathway and their significance in systemic sclerosis - A multilevel analysis

Systemic sclerosis (SSc) or Scleroderma is a complex disease and its etiopathogenesis remains unelucidated. Fibrosis in multiple organs is a key feature of SSc and studies have shown that transforming growth factor-β (TGF-β) pathway has a crucial role in fibrotic responses. For a complex disease such as SSc, expression quantitative trait loci (eQTL) analysis is a powerful tool for identifying genetic variations that affect expression of genes involved in this disease. In this study, a multilevel model is described to perform a multivariate eQTL for identifying genetic variation (SNPs) specifically associated with the expression of three members of TGF-β pathway, CTGF, SPARC and COL3A1. The uniqueness of this model is that all three genes were included in one model, rather than one gene being examined at a time. A protein might contribute to multiple pathways and this approach allows the identification of important genetic variations linked to multiple genes belonging to the same pathway. In this study, 29 SNPs were identified and 16 of them located in known genes. Exploring the roles of these genes in TGF-β regulation will help elucidate the etiology of SSc, which will in turn help to better manage this complex disease. ^

Model results of the impact of climate change on agriculture in China

This paper assesses the impact of climate change on China's agricultural production at a cross-provincial level using the Ricardian approach, incorporating a multilevel model with farm-level group data. The farm-level group data includes 13379 farm households, across 316 villages, distributed in 31 provinces. The empirical results show that, firstly, the marginal effects and elasticities of net crop revenue per hectare with respect to climate factors indicated that the annual impact of temperature on net crop revenue per hectare was positive, and the effect of increased precipitation was negative when looking at the national totals; secondly, the total impact of simulated climate change scenarios on net crop revenues per hectare at a Chinese national total level, was an increase of between 79 USD per hectare and 207 USD per hectare for the 2050s, and an increase from 140 USD per hectare to 355 USD per hectare for the 2080s. As a result, climate change may create a potential advantage for the development of Chinese agriculture, rather than a risk, especially for agriculture in the provinces of the Northeast, Northwest and North regions. However, the increased precipitation can lead to a loss of net crop revenue per hectare, especially for the provinces of the Southwest, Northwest, North and Northeast regions.

A multilevel analysis of team climate and interpersonal exchange relationships at work

This study advances research on interpersonal exchange relationships by integrating social exchange, workplace friendship and climate research to develop a multilevel model. Data were collected from 215 manager-employee dyads working within 36 teams. At the individual level, LMX was positively associated with TMX and workplace friendship. Further, workplace friendship was positively related to TMX, and mediated the LMX-TMX relationship. At the team level, HLM results demonstrated that the relationship between LMX and workplace friendship was moderated by affective climate. Findings suggest that high-quality LMX relationships are associated with enhanced employees' perceptions of workplace friendship when affective group climate was strong.

Managing diversity in organizations:an integrative model and agenda for future research

The literature on policies, procedures, and practices of diversity management in organizations is currently fragmented and often contradictory in highlighting what is effective diversity management, and which organizational and societal factors facilitate or hinder its implementation. In order to provide a comprehensive and cohesive view of diversity management in organizations, we develop a multilevel model informed by the social identity approach that explains, on the basis of a work motivation logic, the processes by, and the conditions under which employee dissimilarity within diverse work groups is related to innovation, effectiveness, and well-being. Building on this new model, we then identify those work group factors (e.g., climate for inclusion and supervisory leadership), organizational factors (e.g., diversity management policies and procedures, and top management's diversity beliefs), and societal factors (e.g., legislation, socioeconomic situation, and culture) that are likely to contribute to the effective management of diversity in organizations. In our discussion of the theoretical implications of the proposed model, we offer a set of propositions to serve as a guide for future research. We conclude with a discussion of possible limitations of the model and practical implications for managing diversity in organizations. © 2014 Taylor & Francis.

Leveraging employee creativity through high performance work systems:a multilevel perspective

Research has looked at single rather than a configuration of human resource management (HRM) practices to influence creativity so it is not yet clear how these practices synergistically facilitate creativity and organisational performance. I address this significant but unanswered question in a three-part study. In Study 1, I develop a high performance work system (HPWS) for creativity scale. I use Study 2 sample to test the validity of the new scale. In Study 3, I test a multilevel model of the intervening processes through which branch HPWS for creativity influences creativity and branch performance. Specifically, at the branch level, I draw on social context theory and hypothesise that branch HPWS for creativity relates to climate for creativity which, in turn, leads to creativity, and ultimately, to profit. Furthermore, I hypothesise environmental dynamism as a boundary condition of the creativity-profit relationship. At the individual level, I hypothesise a cross-level effect of branch HPWS for creativity on employee-perceived HPWS. I draw on self-determination theory and argue that perceived HPWS for creativity relate to need satisfaction and the psychological pathways of intrinsic motivation and creative process engagement to predict creativity. I also hypothesise climate for creativity as a cross-level moderator of the intrinsic motivation-creativity and creative process engagement-creativity relationships. Results of hierarchical linear modeling (HLM) indicate that ten out of the fifteen hypotheses were supported. The findings of this study respond to calls for HPWS to be designed around a strategic focus by developing and providing initial validity evidence of an HPWS for creativity scale. The results reveal the underlying mechanisms through which HPWS for creativity simultaneously influences individual and branch creativity leading to profit. Lastly, results indicate environmental dynamism to be an important boundary condition of the creativity-profit relationship and climate for creativity as a cross-level moderator of the creative process engagement-creativity.

An investigation of the impact of various geographical scales for the specification of spatial dependence

Ecological studies are based on characteristics of groups of individuals, which are common in various disciplines including epidemiology. It is of great interest for epidemiologists to study the geographical variation of a disease by accounting for the positive spatial dependence between neighbouring areas. However, the choice of scale of the spatial correlation requires much attention. In view of a lack of studies in this area, this study aims to investigate the impact of differing definitions of geographical scales using a multilevel model. We propose a new approach -- the grid-based partitions and compare it with the popular census region approach. Unexplained geographical variation is accounted for via area-specific unstructured random effects and spatially structured random effects specified as an intrinsic conditional autoregressive process. Using grid-based modelling of random effects in contrast to the census region approach, we illustrate conditions where improvements are observed in the estimation of the linear predictor, random effects, parameters, and the identification of the distribution of residual risk and the aggregate risk in a study region. The study has found that grid-based modelling is a valuable approach for spatially sparse data while the SLA-based and grid-based approaches perform equally well for spatially dense data.

Supervisor conflict management, justice and strain : multi-level relationships

Purpose The purpose of this paper is to test a multilevel model of the main and mediating effects of supervisor conflict management style (SCMS) climate and procedural justice (PJ) climate on employee strain. It is hypothesized that workgroup-level climate induced by SCMS can fall into four types: collaborative climate, yielding climate, forcing climate, or avoiding climate; that these group-level perceptions will have differential effects on employee strain, and will be mediated by PJ climate. Design/methodology/approach Multilevel SEM was used to analyze data from 420 employees nested in 61 workgroups. Findings Workgroups that perceived high supervisor collaborating climate reported lower sleep disturbance, job dissatisfaction, and action-taking cognitions. Workgroups that perceived high supervisor yielding climate and high supervisor forcing climate reported higher anxiety/depression, sleep disturbance, job dissatisfaction, and action-taking cognitions. Results supported a PJ climate mediation model when supervisors’ behavior was reported to be collaborative and yielding. Research limitations/implications The cross-sectional research design places limitations on conclusions about causality; thus, longitudinal studies are recommended. Practical implications Supervisor behavior in response to conflict may have far-reaching effects beyond those who are a party to the conflict. The more visible use of supervisor collaborative CMS may be beneficial. Social implications The economic costs associated with workplace conflict may be reduced through the application of these findings. Originality/value By applying multilevel theory and analysis, we extend workplace conflict theory.

Koulutuksellisen syrjäytymisriskin ennustettavuus yhteishakuvalintojen kautta tarkasteltuna : koulupudokkuusriskin yhteys oppilaan kognitiiviseen kompetenssiin, koulumenestykseen sekä itseä ja vanhempia koskeviin uskomuksiin

The objective of this study was to find factors that could predict educational dropout. Dropout risk was assessed against pupil’s cognitive competence, success in school, and personal beliefs regarding self and parents, while taking into account the pupil’s background and gender. Based on earlier research, an assumption was made that a pupil’s gender, success in school, and parent’s education would be related with dropping out. This study is part of a project funded by the Academy of Finland and led by Professor Jarkko Hautamäki. The project aims to use longitudinal study to assess the development of pupils’ skills in learning to learn. The target group of this study consisted all Finnish speaking ninth graders of a municipality in Southern Finland. There were in total 1534 pupils, of which 809 were girls and 725 boys. The assessment of learning to learn skills was performed about ninth graders in spring 2004. “Opiopi” test material was used in the assessment, consisting of cognitive tests and questions measuring beliefs. At the same time, pupils’ background information was collected together with their self-reported average grade of all school subjects. During spring 2009, the pupils’ joint application data from years 2004 and 2005 was collected from the Finnish joint application registers. The data were analyzed using quantitative methods assisted by the SPSS for Windows computer software. Analysis was conducted through statistical indices, differences in grade averages, multilevel model, multivariate analysis of variance, and logistic regression analysis. Based on earlier research, dropouts were defined as pupils that had not been admitted to or had not applied to second degree education under the joint application system. Using this definition, 157 students in the target group were classified as dropouts (10 % of the target group): 88 girls and 69 boys. The study showed that the school does not affect the drop-out risk but the school class explains 7,5 % of variation in dropout risk. Among girls, dropping out is predicted by a poor average grade, a lack of beliefs supporting learning, and an unrealistic primary choice in joint application system compared to one’s success in school. Among boys, a poor average grade, unrealistic choices in joint application system, and the belief of parent’s low appreciation of education were related to dropout risk. Keywords educational exclusion, school dropout, success in school, comprehensive school, learning to learn

Um estudo da atenção primária à saúde mediante o indicador: Internações por condições sensíveis à atenção ambulatorial (CSAA)

A Atenção Primária à Saúde - APS é reconhecida como o nível fundamental e porta de entrada do sistema de atenção à saúde, sendo o lugar adequado onde pode ser atendida e resolvida a maior parte dos problemas de saúde. É considerada pela OMS como a principal proposta de modelo assistencial. Essa importância da APS leva a necessidade de pesquisas avaliativas dos seus resultados para adequação e melhoria de políticas e planos de ação delineados em relação à mesma. Pesquisas internacionais e nacionais são realizadas, nas quais indicadores relativos às atividades hospitalares estão sendo empregados com o objetivo de medir resultados como efetividade e acesso da APS. Um desses indicadores, desenvolvido por John Billings da Universidade de Nova York, na década de 90, consiste nas condições pelas quais as internações hospitalares por Condições Sensíveis à Atenção Ambulatorial (CSAA) deveriam ser evitadas caso os serviços da APS fossem efetivos e acessíveis. Utilizando-se o SIH-AIH/2008 e a lista brasileira de Internações por Condições Sensíveis a Atenção Primária, publicada em 2008, a proposta do presente trabalho é a de estudar os cuidados primários à saúde baseando-se nas ICSAA, na área urbana da cidade de Juiz de Fora-MG. Buscou-se responder sobre os efeitos que ocorrem nessas internações a partir das características individuais dos pacientes, das características das Unidades Básicas de Saúde-UBS (infraestrutura, produção e modelos assistenciais) e das condições sócio-econômicas/ambientais das áreas cobertas por UAPS e descobertas (sem UAPS), com a utilização de modelos multiníveis logísticos com intercepto aleatório. Buscou-se conhecer, também, a distribuição espacial das taxas padronizadas por idade das ICSAA nessas áreas e suas associações com as variáveis contextuais, utilizando-se ferramentas da análise espacial. Os resultados do presente trabalho mostraram que a porcentagem de internações por CSAA, foi de 4,1%. Os modelos assistenciais ESF e o Modelo Tradicional, base da organização da atenção primária no Brasil, não apresentaram no município, impacto significativo nas ICSAA, somente na forma de áreas descobertas tendo como referência as áreas cobertas. Também não foram significativas as variáveis de infraestrutura e produção das UAPS. Os efeitos individuais (idade e sexo) nas ICSAA foram significativos, apresentando probabilidades de significância menores que 1%, o mesmo acontecendo com o Índice de Desenvolvimento Social-IDS, que contempla as condições sociais, econômicas e ambientais das áreas analisadas. A distribuição espacial das taxas padronizadas por idade apresentou padrão aleatório e os testes dos Multiplicadores de Lagrange não foram significativos indicando o modelo de regressão clássico (MQO) como adequado para explicar as taxas em função das variáveis contextuais. Para a análise conjunta das áreas cobertas e descobertas foram fatores de risco: a variável econômica (% dos domicílios com renda até 2 SM), áreas descobertas tendo como referência as áreas cobertas e a região nordeste do município. Para as áreas cobertas as variáveis de produção das UAPS, econômica e a região nordeste apresentaram como fator de risco para as taxas de internação por CSAA.

De la cooperativa agroalimentaria a la "learning netchain". Hacia un planteamiento teorico interorganizativo e interpersonal

Se propone un planteamiento teórico/conceptual para determinar si las relaciones interorganizativas e interpersonales de la netchain de las cooperativas agroalimentarias evolucionan hacia una learning netchain. Las propuestas del trabajo muestran que el mayor grado de asociacionismo y la mayor cooperación/colaboración vertical a lo largo de la cadena están positivamente relacionados con la posición horizontal de la empresa focal más cercana del consumidor final. Esto requiere una planificación y una resolución de problemas de manera conjunta, lo que está positivamente relacionado con el mayor flujo y diversidad de la información/conocimiento obtenido y diseminado a lo largo de la netchain. Al mismo tiempo se necesita desarrollar un contexto social en el que fluya la información/conocimiento y las nuevas ideas de manera informal y esto se logra con redes personales y, principalmente, profesionales y con redes internas y, principalmente, externas. Todo esto permitirá una mayor satisfacción de los socios de la cooperativa agroalimentaria y de sus distribuidores y una mayor intensidad en I+D, convirtiéndose la netchain de la cooperativa agroalimentaria, así, en una learning netchain.

Women's Labour Market Performance in Europe: Trends and Shaping Factors. CEPS Special Report, September 2012

We investigate the changes in women’s employment patterns across EU countries over the last 20 years both in terms of labour market participation and type of jobs using individual data from ECHP and EUSILC databases. Using a logistic multilevel model, we then pin down the role played by institutional and policy changes in explaining women’s employment. The key results indicate that women’s employment trends are related to the institutional and policy changes that have been introduced in almost all European countries since the end of the 1990s. Such changes had an important impact on the labour market opportunities’ of women by affecting the quality of potential jobs available, the chances to (re-)enter the labour market and the opportunity costs of employment (vs. non-employment).

Testing white line strength in the dairy cow

The tensile strength of 576 pieces of white line horn collected over 6 mo from 14 dairy cows restricted to parity 1 or 2 was tested. None of the cows had ever been lame. Seven cows were randomly assigned to receive 20 mg/d biotin supplementation, and 7 were not supplemented. Hoof horn samples were taken from zones 2 and 3 (the more proximal and distal sites of the abaxial white line) of the medial and lateral claws of both hind feet on d 1 and on 5 further occasions over 6 mo. The samples were analyzed at 100% water saturation. Hoof slivers were notched to ensure that tensile strength was measured specifically across the white line region. The tensile stress at failure was measured in MPa and was adjusted for the cross-sectional area of the notch site. Data were analyzed in a multilevel model, which accounted for the repeated measures within cows. All other variables were entered as fixed effects. In the final model, there was considerable variation in strength over time. Tensile strength was significantly higher in medial compared with lateral claws, and zone 2 was significantly stronger than zone 3. Where the white line was visibly damaged the tensile strength was low. Biotin supplementation did not affect the tensile strength of the white line. Results of this study indicate that damage to the white line impairs its tensile strength and that in horn with no visible abnormality the white line is weaker in the lateral hind claw than the medial and in zone 3 compared with zone 2. The biomechanical strength was lowest at zone 3 of the lateral hind claw, which is the most common site of white line disease lameness in cattle.

Correspondentes bancários como canal de distribuição de serviços financeiros: taxonomia, histórico, limites e pontencialidades dos modelos de gestão de redes

Adminsitração, análise e tecnologia da informação