925 resultados para hierarchical linear model


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This study explores factors related to the prompt difficulty in Automated Essay Scoring. The sample was composed of 6,924 students. For each student, there were 1-4 essays, across 20 different writing prompts, for a total of 20,243 essays. E-rater® v.2 essay scoring engine developed by the Educational Testing Service was used to score the essays. The scoring engine employs a statistical model that incorporates 10 predictors associated with writing characteristics of which 8 were used. The Rasch partial credit analysis was applied to the scores to determine the difficulty levels of prompts. In addition, the scores were used as outcomes in the series of hierarchical linear models (HLM) in which students and prompts constituted the cross-classification levels. This methodology was used to explore the partitioning of the essay score variance.^ The results indicated significant differences in prompt difficulty levels due to genre. Descriptive prompts, as a group, were found to be more difficult than the persuasive prompts. In addition, the essay score variance was partitioned between students and prompts. The amount of the essay score variance that lies between prompts was found to be relatively small (4 to 7 percent). When the essay-level, student-level-and prompt-level predictors were included in the model, it was able to explain almost all variance that lies between prompts. Since in most high-stakes writing assessments only 1-2 prompts per students are used, the essay score variance that lies between prompts represents an undesirable or "noise" variation. Identifying factors associated with this "noise" variance may prove to be important for prompt writing and for constructing Automated Essay Scoring mechanisms for weighting prompt difficulty when assigning essay score.^

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The current study was a cross-sectional examination of data collected during an HIV risk reduction intervention in south Florida. The purpose of the study was to explore the relationships between neighborhood stress, parenting, attitudes, and adolescent sexual intentions and behavior. The Theory of Planned Behavior was used as a model to guide variable selection and propose an interaction pathway between predictors and outcomes. Potential predictor variables measured for adolescents ages 13–18 (n=196) included communication about sex, parent-family connectedness, parental presence, parent-adolescent activity participation, attitudes about sex and condom use, neighborhood disorder, and exposure to violence. Outcomes were behavioral intentions and sexual behavior for the previous eight months. Neighborhood data was supplemented with ZIP Code level data from regional sources and included median household income, percentage of minority and Hispanic residents, and number of foreclosures. Statistical tests included t-tests, Pearson's correlations, and hierarchical linear regressions. Results showed that males and older adolescents reported less positive behavioral intentions than females and adolescents younger than 16. Intentions were associated with condom attitudes, sexual attitudes, and parental presence; unprotected sexual behavior was associated with parental presence. The best fit model for intentions included gender, sexual attitudes, condom attitudes, parental presence, and neighborhood disorder. The unsafe sexual behavior model included whether the participant lived with both natural parents in the previous year, and the percent of Hispanic residents in the neighborhood. Study findings indicate that more research on adolescent sexual behavior is warranted, specifically examining the differentials between variables that affect intentions and those that affect behavior. A focus on gender and age differences during intervention development may allow for better targeting and more efficacious interventions. Adding peer and media influences to the framework of attitudes, parenting, and neighborhood may offer more insight into patterns of adolescent sexual behavior risk.

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Purpose: Depression in older females is a significant and growing problem. Females who experience life stressors across the life span are at higher risk for developing problems with depression than their male counterparts. The primary aim of this study was (a) to examine gender-specific differences in the correlates of depression in older primary care patients based on baseline and longitudinal analyses; and (b) to examine the longitudinal effect of biopsychosocial risk factors on depression treatment outcomes in different models of behavioral healthcare (i.e., integrated care and enhanced referral). Method: This study used a quantitative secondary data analysis with longitudinal data from the Primary Care Research in Substance Abuse and Mental Health for Elderly (PRISM-E) study. A linear mixed model approach to hierarchical linear modeling was used for analysis using baseline assessment, and follow-up from three-month and six-month. Results: For participants diagnosed with major depressive disorder female gender was associated with increased depression severity at six-month compared to males at six-month. Further, the interaction between gender and life stressors found that females who reported loss of family and friends, family issues, money issues, medical illness was related to higher depression severity compared to males whereas lack of activities was related to lower depression severity among females compared to males. Conclusion: These findings suggest that gender moderated the relationship between specific life stressors and depression severity similar to how a protective factor can impact a person's response to a problem and reduce the negative impact of a risk factor on a problem outcome. Therefore, life stressors may be a reliable predictor of depression for both females and males in either behavioral health treatment model. This study concluded that life stressors influence males basic comfort, stability, and survival whereas life stressors influence females' development, personal growth, and happiness; therefore, life stressors may be a useful component to include in gender-based screening and assessment tools for depression. ^

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We investigate by means of Monte Carlo simulation and finite-size scaling analysis the critical properties of the three dimensional O (5) non-linear σ model and of the antiferromagnetic RP^(2) model, both of them regularized on a lattice. High accuracy estimates are obtained for the critical exponents, universal dimensionless quantities and critical couplings. It is concluded that both models belong to the same universality class, provided that rather non-standard identifications are made for the momentum-space propagator of the RP^(2) model. We have also investigated the phase diagram of the RP^(2) model extended by a second-neighbor interaction. A rich phase diagram is found, where most of the phase transitions are of the first order.

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To effectively assess and mitigate risk of permafrost disturbance, disturbance-p rone areas can be predicted through the application of susceptibility models. In this study we developed regional susceptibility models for permafrost disturbances using a field disturbance inventory to test the transferability of the model to a broader region in the Canadian High Arctic. Resulting maps of susceptibility were then used to explore the effect of terrain variables on the occurrence of disturbances within this region. To account for a large range of landscape charac- teristics, the model was calibrated using two locations: Sabine Peninsula, Melville Island, NU, and Fosheim Pen- insula, Ellesmere Island, NU. Spatial patterns of disturbance were predicted with a generalized linear model (GLM) and generalized additive model (GAM), each calibrated using disturbed and randomized undisturbed lo- cations from both locations and GIS-derived terrain predictor variables including slope, potential incoming solar radiation, wetness index, topographic position index, elevation, and distance to water. Each model was validated for the Sabine and Fosheim Peninsulas using independent data sets while the transferability of the model to an independent site was assessed at Cape Bounty, Melville Island, NU. The regional GLM and GAM validated well for both calibration sites (Sabine and Fosheim) with the area under the receiver operating curves (AUROC) N 0.79. Both models were applied directly to Cape Bounty without calibration and validated equally with AUROC's of 0.76; however, each model predicted disturbed and undisturbed samples differently. Addition- ally, the sensitivity of the transferred model was assessed using data sets with different sample sizes. Results in- dicated that models based on larger sample sizes transferred more consistently and captured the variability within the terrain attributes in the respective study areas. Terrain attributes associated with the initiation of dis- turbances were similar regardless of the location. Disturbances commonly occurred on slopes between 4 and 15°, below Holocene marine limit, and in areas with low potential incoming solar radiation

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We analyze a real data set pertaining to reindeer fecal pellet-group counts obtained from a survey conducted in a forest area in northern Sweden. In the data set, over 70% of counts are zeros, and there is high spatial correlation. We use conditionally autoregressive random effects for modeling of spatial correlation in a Poisson generalized linear mixed model (GLMM), quasi-Poisson hierarchical generalized linear model (HGLM), zero-inflated Poisson (ZIP), and hurdle models. The quasi-Poisson HGLM allows for both under- and overdispersion with excessive zeros, while the ZIP and hurdle models allow only for overdispersion. In analyzing the real data set, we see that the quasi-Poisson HGLMs can perform better than the other commonly used models, for example, ordinary Poisson HGLMs, spatial ZIP, and spatial hurdle models, and that the underdispersed Poisson HGLMs with spatial correlation fit the reindeer data best. We develop R codes for fitting these models using a unified algorithm for the HGLMs. Spatial count response with an extremely high proportion of zeros, and underdispersion can be successfully modeled using the quasi-Poisson HGLM with spatial random effects.

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As an important component in collaborative natural resource management and nonprofit governance, social capital is expected to be related to variations in the performance of land trusts. Land trusts are charitable organizations that work to conserve private land locally, regionally, or nationally. The purpose of this paper is to identify the level of structural and cognitive social capital among local land trusts, and how these two types of social capital relate to the perceived success of land trusts. The analysis integrates data for land trusts operating in the U.S. south-central Appalachian region, which includes western North Carolina, southwest Virginia, and east Tennessee. We use factor analysis to elicit different dimensions of cognitive social capital, including cooperation among board members, shared values, common norms, and communication effectiveness. Measures of structural social capital include the size and diversity of organizational networks of both land trusts and their board members. Finally, a hierarchical linear regression model is employed to estimate how cognitive and structural social capital measures, along with other organizational and individual-level attributes, relate to perceptions of land trust success, defined here as achievement of the land trusts’ mission, conservation, and financial goals. Results show that the diversity of organizational partnerships, cooperation, and shared values among land trust board members are associated with higher levels of perceived success. Organizational capacity, land trust accreditation, volunteerism, and financial support are also important factors influencing perceptions of success among local, nonprofit land trusts.

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This quantitative study examines the impact of teacher practices on student achievement in classrooms where the English is Fun Interactive Radio Instruction (IRI) programs were being used. A contemporary IRI design using a dual-audience approach, the English is Fun IRI programs delivered daily English language instruction to students in grades 1 and 2 in Delhi and Rajasthan through 120 30-minute programs via broadcast radio (the first audience) while modeling pedagogical techniques and behaviors for their teachers (the second audience). Few studies have examined how the dual-audience approach influences student learning. Using existing data from 32 teachers and 696 students, this study utilizes a multivariate multilevel model to examine the role of the primary expectations for teachers (e.g., setting up the IRI classroom, following instructions from the radio characters and ensuring students are participating) and the role of secondary expectations for teachers (e.g., modeling pedagogies and facilitating learning beyond the instructions) in promoting students’ learning in English listening skills, knowledge of vocabulary and use of sentences. The study finds that teacher practice on both sets of expectations mattered, but that practice in the secondary expectations mattered more. As expected, students made the smallest gains in the most difficult linguistic task (sentence use). The extent to which teachers satisfied the primary and secondary expectations was associated with gains in all three skills – confirming the relationship between students’ English proficiency and teacher practice in a dual-audience program. When it came to gains in students’ scores in sentence use, a teacher whose focus was greater on primary expectations had a negative effect on student performance in both states. In all, teacher practice clearly mattered but not in the same way for all three skills. An optimal scenario for teacher practice is presented in which gains in all three skills are maximized. These findings have important implications for the way the classroom teacher is cast in IRI programs that utilize a dual-audience approach and in the way IRI programs are contracted insofar as the role of the teacher in instruction is minimized and access is limited to instructional support from the IRI lessons alone.

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The municipal management in any country of the globe requires planning and allocation of resources evenly. In Brazil, the Law of Budgetary Guidelines (LDO) guides municipal managers toward that balance. This research develops a model that seeks to find the balance of the allocation of public resources in Brazilian municipalities, considering the LDO as a parameter. For this using statistical techniques and multicriteria analysis as a first step in order to define allocation strategies, based on the technical aspects arising from the municipal manager. In a second step, presented in linear programming based optimization where the objective function is derived from the preference of the results of the manager and his staff. The statistical representation is presented to support multicriteria development in the definition of replacement rates through time series. The multicriteria analysis was structured by defining the criteria, alternatives and the application of UTASTAR methods to calculate replacement rates. After these initial settings, an application of linear programming was developed to find the optimal allocation of enforcement resources of the municipal budget. Data from the budget of a municipality in southwestern Paraná were studied in the application of the model and analysis of results.

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We investigate the secular dynamics of three-body circumbinary systems under the effect of tides. We use the octupolar non-restricted approximation for the orbital interactions, general relativity corrections, the quadrupolar approximation for the spins, and the viscous linear model for tides. We derive the averaged equations of motion in a simplified vectorial formalism, which is suitable to model the long-term evolution of a wide variety of circumbinary systems in very eccentric and inclined orbits. In particular, this vectorial approach can be used to derive constraints for tidal migration, capture in Cassini states, and stellar spin–orbit misalignment. We show that circumbinary planets with initial arbitrary orbital inclination can become coplanar through a secular resonance between the precession of the orbit and the precession of the spin of one of the stars. We also show that circumbinary systems for which the pericenter of the inner orbit is initially in libration present chaotic motion for the spins and for the eccentricity of the outer orbit. Because our model is valid for the non-restricted problem, it can also be applied to any three-body hierarchical system such as star–planet–satellite systems and triple stellar systems.

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The milling of thin parts is a high added value operation where the machinist has to face the chatter problem. The study of the stability of these operations is a complex task due to the changing modal parameters as the part loses mass during the machining and the complex shape of the tools that are used. The present work proposes a methodology for chatter avoidance in the milling of flexible thin floors with a bull-nose end mill. First, a stability model for the milling of compliant systems in the tool axis direction with bull-nose end mills is presented. The contribution is the averaging method used to be able to use a linear model to predict the stability of the operation. Then, the procedure for the calculation of stability diagrams for the milling of thin floors is presented. The method is based on the estimation of the modal parameters of the part and the corresponding stability lobes during the machining. As in thin floor milling the depth of cut is already defined by the floor thickness previous to milling, the use of stability diagrams that relate the tool position along the tool-path with the spindle speed is proposed. Hence, the sequence of spindle speeds that the tool must have during the milling can be selected. Finally, this methodology has been validated by means of experimental tests.

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Resumo: Registros de sobrevivência do nascimento ao desmame de 3846 crias de ovinos da raça Santa Inês foram analisados por modelos de reprodutor linear e não linear (modelo de limiar), para estimar componentes de variância e herdabilidade. Os modelos usados para sobrevivência, analisada como característica da cria, incluíram os efeitos fixos de sexo, da combinação tipo de nascimento-criação da cria e da idade da ovelha ao parto, efeito da covariável peso da cria ao nascer e efeitos aleatórios de reprodutor, da classe rebanho-ano-estação e do resíduo. Componentes de variância para o modelo linear foram estimados pelo método da máxima verossimilhança restrita (REML) e para o modelo não linear por uma aproximação da máxima verossimilhança marginal (MML), pelo programa CMMAT2. O coeficiente de herdabilidade (h2) estimado pelo modelo de limiar foi de 0,29, e pelo modelo linear, 0,14. A correlação de ordem de Spearman entre as capacidades de transmissão dos reprodutores, com base nos dois modelos foi de 0,96. As estimativas de h2 obtidas indicam a possibilidade de se obter, por seleção, ganho genético para sobrevivência. [Linear and nonlinear models in genetic analyses of lamb survival in the Santa Inês hair sheep breed]. Abstract: Records of 3,846 lambs survival from birth to weaning of Santa Inês hair sheep breed, were analyzed by linear and non linear sire models (threshold model) to estimate variance components and heritability (h2). The models that were used to analyze survival, considered in this study as a lamb trait, included the fixed effects of sex of the lamb, combination of type of birth-rearing of lamb, and age of ewe, birth weight of lamb as covariate, and random effects of sire, herd-year-season and residual. Variance components were obtained using restricted maximum likelihood (REML), in linear model and marginal maximum likelihood in threshold model through CMMAT2 program. Estimate of heritability (h2) obtained by threshold model was 0.29 and by linear model was 0.14. Rank correlation of Spearman, between sire solutions based on the two models was 0.96. The obtained estimates in this study indicate that it is possible to acquire genetic gain to survival by selection.

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The current study was a cross-sectional examination of data collected during an HIV risk reduction intervention in south Florida. The purpose of the study was to explore the relationships between neighborhood stress, parenting, attitudes, and adolescent sexual intentions and behavior. The Theory of Planned Behavior was used as a model to guide variable selection and propose an interaction pathway between predictors and outcomes. Potential predictor variables measured for adolescents ages 13-18 (n=196) included communication about sex, parent-family connectedness, parental presence, parent-adolescent activity participation, attitudes about sex and condom use, neighborhood disorder, and exposure to violence. Outcomes were behavioral intentions and sexual behavior for the previous eight months. Neighborhood data was supplemented with ZIP Code level data from regional sources and included median household income, percentage of minority and Hispanic residents, and number of foreclosures. Statistical tests included t-tests, Pearson’s correlations, and hierarchical linear regressions. Results showed that males and older adolescents reported less positive behavioral intentions than females and adolescents younger than 16. Intentions were associated with condom attitudes, sexual attitudes, and parental presence; unprotected sexual behavior was associated with parental presence. The best fit model for intentions included gender, sexual attitudes, condom attitudes, parental presence, and neighborhood disorder. The unsafe sexual behavior model included whether the participant lived with both natural parents in the previous year, and the percent of Hispanic residents in the neighborhood. Study findings indicate that more research on adolescent sexual behavior is warranted, specifically examining the differentials between variables that affect intentions and those that affect behavior. A focus on gender and age differences during intervention development may allow for better targeting and more efficacious interventions. Adding peer and media influences to the framework of attitudes, parenting, and neighborhood may offer more insight into patterns of adolescent sexual behavior risk.

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Students negotiate the transition to secondary school in different ways. While some thrive on the opportunity, others are challenged. A prospective longitudinal design was used to determine the contribution of personal background and school contextual factors on academic competence (AC) and mental health functioning (MHF) of 266 students, 6-months before and after the transition to secondary school. Data from 197 typically developing students and 69 students with a disability were analysed using hierarchical linear regression modelling. Both in primary and secondary school, students with a disability and from socially disadvantaged backgrounds gained poorer scores for AC and MHF than their typically developing and more affluent counterparts. Students who attended independent and mid-range sized primary schools had the highest concurrent AC. Those from independent primary schools had the lowest MHF. The primary school organisational model significantly influenced post-transition AC scores; with students from Kindergarten--Year 7 schools reporting the lowest scores, while those from the Kindergarten--Year 12 structure without middle school having the highest scores. Attending a school which used the Kindergarten--Year 12 with middle school structure was associated with a reduction in AC scores across the transition. Personal background factors accounted for the majority of the variability in post-transition AC and MHF. The contribution of school contextual factors was relatively minor. There is a potential opportunity for schools to provide support to disadvantaged students before the transition to secondary school, as they continue to be at a disadvantage after the transition.

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We present a multiscale model bridging length and time scales from molecular to continuum levels with the objective of predicting the yield behavior of amorphous glassy polyethylene (PE). Constitutive pa- rameters are obtained from molecular dynamics (MD) simulations, decreasing the requirement for ad- hoc experiments. Consequently, we achieve: (1) the identification of multisurface yield functions; (2) the high strain rate involved in MD simulations is upscaled to continuum via quasi-static simulations. Validation demonstrates that the entire multisurface yield functions can be scaled to quasi-static rates where the yield stresses are possibly predicted by a proposed scaling law; (3) a hierarchical multiscale model is constructed to predict temperature and strain rate dependent yield strength of the PE.