Meteorological influences on the interannual variability of meningitis incidence in northwest Nigeria.

NASA Astrophysics Data System (ADS)

Abdussalam, Auwal; Monaghan, Andrew; Dukic, Vanja; Hayden, Mary; Hopson, Thomas; Leckebusch, Gregor

2013-04-01

Northwest Nigeria is a region with high risk of bacterial meningitis. Since the first documented epidemic of meningitis in Nigeria in 1905, the disease has been endemic in the northern part of the country, with epidemics occurring regularly. In this study we examine the influence of climate on the interannual variability of meningitis incidence and epidemics. Monthly aggregate counts of clinically confirmed hospital-reported cases of meningitis were collected in northwest Nigeria for the 22-year period spanning 1990-2011. Several generalized linear statistical models were fit to the monthly meningitis counts, including generalized additive models. Explanatory variables included monthly records of temperatures, humidity, rainfall, wind speed, sunshine and dustiness from weather stations nearest to the hospitals, and a time series of polysaccharide vaccination efficacy. The effects of other confounding factors -- i.e., mainly non-climatic factors for which records were not available -- were estimated as a smooth, monthly-varying function of time in the generalized additive models. Results reveal that the most important explanatory climatic variables are mean maximum monthly temperature, relative humidity and dustiness. Accounting for confounding factors (e.g., social processes) in the generalized additive models explains more of the year-to-year variation of meningococcal disease compared to those generalized linear models that do not account for such factors. Promising results from several models that included only explanatory variables that preceded the meningitis case data by 1-month suggest there may be potential for prediction of meningitis in northwest Nigeria to aid decision makers on this time scale.

Body Fat Percentage Prediction Using Intelligent Hybrid Approaches

PubMed Central

Shao, Yuehjen E.

2014-01-01

Excess of body fat often leads to obesity. Obesity is typically associated with serious medical diseases, such as cancer, heart disease, and diabetes. Accordingly, knowing the body fat is an extremely important issue since it affects everyone's health. Although there are several ways to measure the body fat percentage (BFP), the accurate methods are often associated with hassle and/or high costs. Traditional single-stage approaches may use certain body measurements or explanatory variables to predict the BFP. Diverging from existing approaches, this study proposes new intelligent hybrid approaches to obtain fewer explanatory variables, and the proposed forecasting models are able to effectively predict the BFP. The proposed hybrid models consist of multiple regression (MR), artificial neural network (ANN), multivariate adaptive regression splines (MARS), and support vector regression (SVR) techniques. The first stage of the modeling includes the use of MR and MARS to obtain fewer but more important sets of explanatory variables. In the second stage, the remaining important variables are served as inputs for the other forecasting methods. A real dataset was used to demonstrate the development of the proposed hybrid models. The prediction results revealed that the proposed hybrid schemes outperformed the typical, single-stage forecasting models. PMID:24723804

An Institutional Model of Organizational Practice: Financial Reporting at the Fortune 200.

ERIC Educational Resources Information Center

Mezias, Stephen J.

1990-01-01

Compares applied economic models and an institutional model in an empirical study of financial reporting practice at the Fortune 200 between 1962 and 1984. Findings indicate that the institutional model adds significant explanatory power over and above the models currently dominating the applied economics literature. Includes 47 references. (MLH)

Comparison of watershed disturbance predictive models for stream benthic macroinvertebrates for three distinct ecoregions in western US

USGS Publications Warehouse

Waite, Ian R.; Brown, Larry R.; Kennen, Jonathan G.; May, Jason T.; Cuffney, Thomas F.; Orlando, James L.; Jones, Kimberly A.

2010-01-01

The successful use of macroinvertebrates as indicators of stream condition in bioassessments has led to heightened interest throughout the scientific community in the prediction of stream condition. For example, predictive models are increasingly being developed that use measures of watershed disturbance, including urban and agricultural land-use, as explanatory variables to predict various metrics of biological condition such as richness, tolerance, percent predators, index of biotic integrity, functional species traits, or even ordination axes scores. Our primary intent was to determine if effective models could be developed using watershed characteristics of disturbance to predict macroinvertebrate metrics among disparate and widely separated ecoregions. We aggregated macroinvertebrate data from universities and state and federal agencies in order to assemble stream data sets of high enough density appropriate for modeling in three distinct ecoregions in Oregon and California. Extensive review and quality assurance of macroinvertebrate sampling protocols, laboratory subsample counts and taxonomic resolution was completed to assure data comparability. We used widely available digital coverages of land-use and land-cover data summarized at the watershed and riparian scale as explanatory variables to predict macroinvertebrate metrics commonly used by state resource managers to assess stream condition. The “best” multiple linear regression models from each region required only two or three explanatory variables to model macroinvertebrate metrics and explained 41–74% of the variation. In each region the best model contained some measure of urban and/or agricultural land-use, yet often the model was improved by including a natural explanatory variable such as mean annual precipitation or mean watershed slope. Two macroinvertebrate metrics were common among all three regions, the metric that summarizes the richness of tolerant macroinvertebrates (RICHTOL) and some form of EPT (Ephemeroptera, Plecoptera, and Trichoptera) richness. Best models were developed for the same two invertebrate metrics even though the geographic regions reflect distinct differences in precipitation, geology, elevation, slope, population density, and land-use. With further development, models like these can be used to elicit better causal linkages to stream biological attributes or condition and can be used by researchers or managers to predict biological indicators of stream condition at unsampled sites.

"Head take you": causal attributions of mental illness in Jamaica.

PubMed

Arthur, Carlotta M; Whitley, Rob

2015-02-01

Causal attributions are a key factor in explanatory models of illness; however, little research on causal attributions of mental illness has been conducted in developing nations in the Caribbean, including Jamaica. Explanatory models of mental illness may be important in understanding illness experience and be a crucial factor in mental health service seeking and utilization. We explored causal attributions of mental illness in Jamaica by conducting 20 focus groups, including 16 community samples, 2 patient samples, and 2 samples of caregivers of patients, with a total of 159 participants. The 5 most commonly endorsed causal attributions of mental illness are discussed: (a) drug-related causes, including ganja (marijuana); (b) biological causes, such as chemical imbalance, familial transmission, and "blood"; (c) psychological causes, including stress and thinking too much; (d) social causes, such as relationship problems and job loss; and (e) spiritual or religious causes, including Obeah. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Insight in psychosis: Standards, science, ethics and value judgment.

PubMed

Jacob, K S

2017-06-01

The clinical assessment of insight solely employs biomedical perspectives and criteria to the complete exclusion of context and culture and to the disregard of values and value judgments. The aim of this discussion article is to examine recent research from India on insight and explanatory models in psychosis and re-examine the framework of assessment, diagnosis and management of insight and explanatory models. Recent research from India on insight in psychosis and explanatory models is reviewed. Recent research, which has used longitudinal data and adjusted for pretreatment variables, suggests that insight and explanatory models of illness at baseline do not predict course, outcome and treatment response in schizophrenia, which seem to be dependent on the severity and quality of the psychosis. It supports the view that people with psychosis simultaneously hold multiple and contradictory explanatory models of illness, which change over time and with the trajectory of the illness. It suggests that insight, like all explanatory models, is a narrative of the person's reality and a coping strategy to handle with the varied impact of the illness. This article argues that the assessment of insight necessarily involves value entailments, commitments and consequences. It supports a need for a broad-based approach to assess awareness, attribution and action related to mental illness and to acknowledge the role of values and value judgment in the evaluation of insight in psychosis.

Explanatory models of diabetes in urban poor communities in Accra, Ghana.

PubMed

de-Graft Aikins, Ama; Awuah, Raphael Baffour; Pera, Tuula Anneli; Mendez, Montserrat; Ogedegbe, Gbenga

2015-01-01

The objective of the study was to examine explanatory models of diabetes and diabetes complications among urban poor Ghanaians living with diabetes and implications for developing secondary prevention strategies. Twenty adults with type 2 diabetes were recruited from three poor communities in Accra. Qualitative data were obtained using interviews that run between 40 and 90 minutes. The interviews were audio-taped, transcribed and analysed thematically, informed by the 'explanatory model of disease' concept. Respondents associated diabetes and its complications with diet, family history, lifestyle factors (smoking, excessive alcohol consumption and physical inactivity), psychological stress and supernatural factors (witchcraft and sorcery). These associations were informed by biomedical and cultural models of diabetes and disease. Subjective experience, through a process of 'body-listening,' constituted a third model on which respondents drew to theorise diabetes complications. Poverty was an important mediator of poor self-care practices, including treatment non-adherence. The biomedical model of diabetes was a major source of legitimate information for self-care practices. However, this was understood and applied through a complex framework of cultural theories of chronic disease, the biopsychological impact of everyday illness experience and the disempowering effects of poverty. An integrated biopsychosocial approach is proposed for diabetes intervention in this research community.

Insight, psychopathology, explanatory models and outcome of schizophrenia in India: a prospective 5-year cohort study.

PubMed

Johnson, Shanthi; Sathyaseelan, Manoranjitham; Charles, Helen; Jeyaseelan, Visalakshi; Jacob, Kuruthukulangara Sebastian

2012-09-27

The sole focus of models of insight on bio-medical perspectives to the complete exclusion of local, non-medical and cultural constructs mandates review. This study attempted to investigate the impact of insight, psychopathology, explanatory models of illness on outcome of first episode schizophrenia. Patients diagnosed to have DSM IV schizophrenia (n = 131) were assessed prospectively for insight, psychopathology, explanatory models of illness at baseline, 6, 12 and 60 months using standard instruments. Multiple linear and logistic regression and generalized estimating equations (GEE) were employed to assess predictors of outcome. We could follow up 95 (72.5%) patients. Sixty-five of these patients (68.4%) achieved remission. There was a negative relationship between psychosis rating and insight scores. Urban residence, fluctuating course of the initial illness, and improvement in global functioning at 6 months and lower psychosis rating at 12 months were significantly related to remission at 5 years. Insight scores, number of non-medical explanatory models and individual explanatory models held during the later course of the illness were significantly associated with outcome. Analysis of longitudinal data using GEE showed that women, rural residence, insight scores and number of non-medical explanatory models of illness held were significantly associated with BPRS scores during the study period. Insight, the disease model and the number of non-medical model positively correlated with improvement in psychosis arguing for a complex interaction between the culture, context and illness variables. These finding argue that insight and explanatory models are secondary to psychopathology, course and outcome of the illness. The awareness of mental illness is a narrative act in which people make personal sense of the many challenges they face. The course and outcome of the illness, cultural context, acceptable cultural explanations and the prevalent social stigma interact to produce a complex and multifaceted understanding of the issues. This complexity calls for a nuanced framing of insight.

Explanatory models in patients with first episode depression: a study from north India.

PubMed

Grover, Sandeep; Kumar, Vineet; Chakrabarti, Subho; Hollikatti, Prabhakar; Singh, Pritpal; Tyagi, Shikha; Kulhara, Parmanand; Avasthi, Ajit

2012-09-01

The purpose of this work was to study the explanatory models of patients with first episode depression presenting to a tertiary care hospital located in North-western India. One hundred sixty four consecutive patients with diagnosis of first episode depression (except severe depression with psychotic symptoms) according to the International Classification of Diseases-10th Revision (ICD-10) and ≥18 years of age were evaluated for their explanatory models using the causal models section of Explanatory Model Interview Catalogue (EMIC). The most common explanations given were categorized into Karma-deed-heredity category (77.4%), followed by psychological explanations (62.2%), weakness (50%) and social causes (40.2%). Among the various specific causes the commonly reported explanations by at least one-fourth of the sample in decreasing order were: will of god (51.2%), fate/chance (40.9%), weakness of nerves (37.8%), general weakness (34.7%), bad deeds (26.2%), evil eye (24.4%) and family problems (21.9%). There was some influence of sociodemographic features on the explanations given by the patients. From the study, it can be concluded that patients with first episode depression have multiple explanatory models for their symptoms of depression which are slightly different than those reported in previous studies done from other parts of India. Understanding the multiple explanatory models for their symptoms of depression can have important treatment implications. Copyright © 2012 Elsevier B.V. All rights reserved.

Spatially Resolved Measurements Of Plasma Density Irregularities In The Ionosphere F Region For Scintillation Studies.

NASA Astrophysics Data System (ADS)

Spencer, E. A.; Russ, S.; Clark, D. C.; Latif, S.; Montalvo, C.

2016-12-01

This qualitative study focuses on students evidence-based explanatory models on how ocean acidification impacts oysters. Explanatory models are the crucial components of scientific endeavors as it helps scientists explain how the natural world functions and the reasons for the ways it functions. Moreover, these models assemble individual practices to understand how they work together to reach clear conclusions through scientific investigations. Due to their critical roles in making sense of authentic science, recent studies in science education suggest that these models should be part of the curriculum aligned with new science standards, i.e. Next Generation Science Standards, which stress the importance of engaging students in scientific practices. By collecting data from 400 secondary school students in Maryland, we aim to respond to the question: How can we use secondary school students' explanatory models to provide students with constructive feedback for more comprehensive learning of ocean acidification (the related evidence, causes and impact)? The data were analyzed through discourse analysis method. We highlighted and coded students' inscriptions (e.g., drawings, writings, and representations) that are signs of students' understanding (or lack thereof) of ocean acidification. These signs included explanations of pH levels, drawings of oyster growth, and inclusions of relevant data. The findings showed that the explanatory models can be critical forms of feedback as they reveal a) students' alternative conceptions on how ocean acidification impacts oysters or how acidification works in general; b) students' interpretations of oceans' (non)connectedness to Earth system; c) the choice of scientific representations and their sources; and d) the way students' integrate evidence or data from the investigations. Our work tackles an understanding of one of the most vital signs of modern climatic changes. Recent scientific evidence shows that if the change in ocean pH becomes too extreme, many organisms may not be able to adjust to this change. Based on our findings, we suggest that teachers can use explanatory models as sources of feedback to recognize how well their students conceptualize ocean acidification, integrate scientific practices, and use cultural artifacts of doing science.

Predicting daily use of urban forest recreation sites

Treesearch

John F. Dwyer

1988-01-01

A multiple linear regression model explains 90% of the variance in daily use of an urban recreation site. Explanatory variables include season, day of the week, and weather. The results offer guides for recreation site planning and management as well as suggestions for improving the model.

Sexual function in women in rural Tamil Nadu: disease, dysfunction, distress and norms.

PubMed

Viswanathan, Shonima; Prasad, Jasmine; Jacob, K S; Kuruvilla, Anju

2014-01-01

We examined the nature, prevalence and explanatory models of sexual concerns and dysfunction among women in rural Tamil Nadu. Married women between 18 and 65 years of age, from randomly selected villages in Kaniyambadi block, Vellore district, Tamil Nadu, were chosen by stratified sampling technique. Sexual functioning was assessed using the Female Sexual Function Index (FSFI). The modified Short Explanatory Model Interview (SEMI) was used to assess beliefs about sexual concerns and the General Health Questionnaire-12 (GHQ-12) was used to screen for common mental disorders. Sociodemographic variables and other risk factors were also assessed. Most of the women (277; 98.2%) contacted agreed to participate in the study. The prevalence of sexual dysfunction, based on the cut-off score on the FSFI, was 64.3%. However, only a minority of women considered it a problem (4.7%), expressed dissatisfaction (5.8%) or sought medical help (2.5%). The most common explanatory models offered for sexual problems included an unhappy marriage,stress and physical problems. Factors associated with lower FSFI included older age, illiteracy, as well as medical illness and sexual and marital factors such as menopause, poor quality of marital relationship, history of physical abuse and lack of privacy. The diagnosis of female sexual dysfunction needs to be nuanced and based on the broader personal and social context. Our findings argue that there is a need to use models that employ personal, local and contextual standards in assessing complex behaviours such as sexual function. Copyright 2014, NMJI.

Dietary restrictions in healing among speakers of Iquito, an endangered language of the Peruvian Amazon

PubMed Central

2011-01-01

Background Ethnobotanical research was carried out with speakers of Iquito, a critically endangered Amazonian language of the Zaparoan family. The study focused on the concept of "dieting" (siyan++ni in Iquito), a practice involving prohibitions considered necessary to the healing process. These restrictions include: 1) foods and activities that can exacerbate illness, 2) environmental influences that conflict with some methods of healing (e.g. steam baths or enemas) and 3) foods and activities forbidden by the spirits of certain powerful medicinal plants. The study tested the following hypotheses: H1 - Each restriction will correlate with specific elements in illness explanatory models and H2 - Illnesses whose explanatory models have personalistic elements will show a greater number and variety of restrictions than those based on naturalistic reasoning. Methods The work was carried out in 2009 and 2010 in the Alto Nanay region of Peru. In structured interviews, informants gave explanatory models for illness categories, including etiologies, pathophysiologies, treatments and dietary restrictions necessary for 49 illnesses. Seventeen botanical vouchers for species said to have powerful spirits that require diets were also collected. Results All restrictions found correspond to some aspect of illness explanatory models. Thirty-five percent match up with specific illness etiologies, 53% correspond to particular pathophysiologies, 18% correspond with overall seriousness of the illness and 18% are only found with particular forms of treatment. Diets based on personalistic reasoning have a significantly higher average number of restrictions than those based on naturalistic reasoning. Conclusions Dieting plays a central role in healing among Iquito speakers. Specific prohibitions can be explained in terms of specific aspects of illness etiologies, pathophysiologies and treatments. Although the Amazonian literature contains few studies focusing on dietary proscriptions over a wide range of illnesses, some specific restrictions reported here do correspond with trends seen in other Amazonian societies, particularly those related to sympathetic reasoning and for magical and spiritual uses of plants. PMID:21745400

Dietary restrictions in healing among speakers of Iquito, an endangered language of the Peruvian Amazon.

PubMed

Jernigan, Kevin A

2011-07-11

Ethno botanical research was carried out with speakers of Iquitos, a critically endangered Amazonian language of the Zaparoan family. The study focused on the concept of "dieting" (siyan++ni in Iquitos), a practice involving prohibitions considered necessary to the healing process. These restrictions include: 1) foods and activities that can exacerbate illness, 2) environmental influences that conflict with some methods of healing (e.g. steam baths or enemas) and 3) foods and activities forbidden by the spirits of certain powerful medicinal plants. The study tested the following hypotheses: H1--Each restriction will correlate with specific elements in illness explanatory models and H2--Illnesses whose explanatory models have personality elements will show a greater number and variety of restrictions than those based on naturalistic reasoning. The work was carried out in 2009 and 2010 in the Alto Nanay region of Peru. In structured interviews, informants gave explanatory models for illness categories, including etiologies, pathophysiologies, treatments and dietary restrictions necessary for 49 illnesses. Seventeen botanical vouchers for species said to have powerful spirits that require diets were also collected. All restrictions found correspond to some aspect of illness explanatory models. Thirty-five percent match up with specific illness etiologies, 53% correspond to particular pathophysiologies, 18% correspond with overall seriousness of the illness and 18% are only found with particular forms of treatment. Diets based on personalistic reasoning have a significantly higher average number of restrictions than those based on naturalistic reasoning. Dieting plays a central role in healing among Iquitos speakers. Specific prohibitions can be explained in terms of specific aspects of illness etiologies, pathophysiologies and treatments. Although the Amazonian literature contains few studies focusing on dietary proscriptions over a wide range of illnesses, some specific restrictions reported here do correspond with trends seen in other Amazonian societies, particularly those related to sympathetic reasoning and for magical and spiritual uses of plants.

Empirical spatial econometric modelling of small scale neighbourhood

NASA Astrophysics Data System (ADS)

Gerkman, Linda

2012-07-01

The aim of the paper is to model small scale neighbourhood in a house price model by implementing the newest methodology in spatial econometrics. A common problem when modelling house prices is that in practice it is seldom possible to obtain all the desired variables. Especially variables capturing the small scale neighbourhood conditions are hard to find. If there are important explanatory variables missing from the model, the omitted variables are spatially autocorrelated and they are correlated with the explanatory variables included in the model, it can be shown that a spatial Durbin model is motivated. In the empirical application on new house price data from Helsinki in Finland, we find the motivation for a spatial Durbin model, we estimate the model and interpret the estimates for the summary measures of impacts. By the analysis we show that the model structure makes it possible to model and find small scale neighbourhood effects, when we know that they exist, but we are lacking proper variables to measure them.

Cross-cultural perspectives on physician and lay models of the common cold.

PubMed

Baer, Roberta D; Weller, Susan C; de Alba García, Javier García; Rocha, Ana L Salcedo

2008-06-01

We compare physicians and laypeople within and across cultures, focusing on similarities and differences across samples, to determine whether cultural differences or lay-professional differences have a greater effect on explanatory models of the common cold. Data on explanatory models for the common cold were collected from physicians and laypeople in South Texas and Guadalajara, Mexico. Structured interview materials were developed on the basis of open-ended interviews with samples of lay informants at each locale. A structured questionnaire was used to collect information from each sample on causes, symptoms, and treatments for the common cold. Consensus analysis was used to estimate the cultural beliefs for each sample. Instead of systematic differences between samples based on nationality or level of professional training, all four samples largely shared a single-explanatory model of the common cold, with some differences on subthemes, such as the role of hot and cold forces in the etiology of the common cold. An evaluation of our findings indicates that, although there has been conjecture about whether cultural or lay-professional differences are of greater importance in understanding variation in explanatory models of disease and illness, systematic data collected on community and professional beliefs indicate that such differences may be a function of the specific illness. Further generalizations about lay-professional differences need to be based on detailed data for a variety of illnesses, to discern patterns that may be present. Finally, a systematic approach indicates that agreement across individual explanatory models is sufficient to allow for a community-level explanatory model of the common cold.

Consumer-operated service program members' explanatory models of mental illness and recovery.

PubMed

Hoy, Janet M

2014-10-01

Incorporating individuals' understandings and explanations of mental illness into service delivery offers benefits relating to increased service relevance and meaning. Existing research delineates explanatory models of mental illness held by individuals in home, outpatient, and hospital-based contexts; research on models held by those in peer-support contexts is notably absent. In this article, I describe themes identified within and across explanatory models of mental illness and recovery held by mental health consumers (N = 24) at one peer center, referred to as a consumer-operated service center (COSP). Participants held explanatory models inclusive of both developmental stressors and biomedical causes, consistent with a stress-diathesis model (although no participant explicitly referenced such). Explicit incorporation of stress-diathesis constructs into programming at this COSP offers the potential of increasing service meaning and relevance. Identifying and incorporating shared meanings across individuals' understandings of mental illness likewise can increase relevance and meaning for particular subgroups of service users. © The Author(s) 2014.

Modeling Effects of Temperature, Soil, Moisture, Nutrition and Variety As Determinants of Severity of Pythium Damping-Off and Root Disease in Subterranean Clover

PubMed Central

You, Ming P.; Rensing, Kelly; Renton, Michael; Barbetti, Martin J.

2017-01-01

Subterranean clover (Trifolium subterraneum) is a critical pasture legume in Mediterranean regions of southern Australia and elsewhere, including Mediterranean-type climatic regions in Africa, Asia, Australia, Europe, North America, and South America. Pythium damping-off and root disease caused by Pythium irregulare is a significant threat to subterranean clover in Australia and a study was conducted to define how environmental factors (viz. temperature, soil type, moisture and nutrition) as well as variety, influence the extent of damping-off and root disease as well as subterranean clover productivity under challenge by this pathogen. Relationships were statistically modeled using linear and generalized linear models and boosted regression trees. Modeling found complex relationships between explanatory variables and the extent of Pythium damping-off and root rot. Linear modeling identified high-level (4 or 5-way) significant interactions for each dependent variable (dry shoot and root weight, emergence, tap and lateral root disease index). Furthermore, all explanatory variables (temperature, soil, moisture, nutrition, variety) were found significant as part of some interaction within these models. A significant five-way interaction between all explanatory variables was found for both dry shoot and root dry weights, and a four way interaction between temperature, soil, moisture, and nutrition was found for both tap and lateral root disease index. A second approach to modeling using boosted regression trees provided support for and helped clarify the complex nature of the relationships found in linear models. All explanatory variables showed at least 5% relative influence on each of the five dependent variables. All models indicated differences due to soil type, with the sand-based soil having either higher weights, greater emergence, or lower disease indices; while lowest weights and less emergence, as well as higher disease indices, were found for loam soil and low temperature. There was more severe tap and lateral root rot disease in higher moisture situations. PMID:29184544

Reporting and Methodology of Multivariable Analyses in Prognostic Observational Studies Published in 4 Anesthesiology Journals: A Methodological Descriptive Review.

PubMed

Guglielminotti, Jean; Dechartres, Agnès; Mentré, France; Montravers, Philippe; Longrois, Dan; Laouénan, Cedric

2015-10-01

Prognostic research studies in anesthesiology aim to identify risk factors for an outcome (explanatory studies) or calculate the risk of this outcome on the basis of patients' risk factors (predictive studies). Multivariable models express the relationship between predictors and an outcome and are used in both explanatory and predictive studies. Model development demands a strict methodology and a clear reporting to assess its reliability. In this methodological descriptive review, we critically assessed the reporting and methodology of multivariable analysis used in observational prognostic studies published in anesthesiology journals. A systematic search was conducted on Medline through Web of Knowledge, PubMed, and journal websites to identify observational prognostic studies with multivariable analysis published in Anesthesiology, Anesthesia & Analgesia, British Journal of Anaesthesia, and Anaesthesia in 2010 and 2011. Data were extracted by 2 independent readers. First, studies were analyzed with respect to reporting of outcomes, design, size, methods of analysis, model performance (discrimination and calibration), model validation, clinical usefulness, and STROBE (i.e., Strengthening the Reporting of Observational Studies in Epidemiology) checklist. A reporting rate was calculated on the basis of 21 items of the aforementioned points. Second, they were analyzed with respect to some predefined methodological points. Eighty-six studies were included: 87.2% were explanatory and 80.2% investigated a postoperative event. The reporting was fairly good, with a median reporting rate of 79% (75% in explanatory studies and 100% in predictive studies). Six items had a reporting rate <36% (i.e., the 25th percentile), with some of them not identified in the STROBE checklist: blinded evaluation of the outcome (11.9%), reason for sample size (15.1%), handling of missing data (36.0%), assessment of colinearity (17.4%), assessment of interactions (13.9%), and calibration (34.9%). When reported, a few methodological shortcomings were observed, both in explanatory and predictive studies, such as an insufficient number of events of the outcome (44.6%), exclusion of cases with missing data (93.6%), or categorization of continuous variables (65.1%.). The reporting of multivariable analysis was fairly good and could be further improved by checking reporting guidelines and EQUATOR Network website. Limiting the number of candidate variables, including cases with missing data, and not arbitrarily categorizing continuous variables should be encouraged.

Spatial generalised linear mixed models based on distances.

PubMed

Melo, Oscar O; Mateu, Jorge; Melo, Carlos E

2016-10-01

Risk models derived from environmental data have been widely shown to be effective in delineating geographical areas of risk because they are intuitively easy to understand. We present a new method based on distances, which allows the modelling of continuous and non-continuous random variables through distance-based spatial generalised linear mixed models. The parameters are estimated using Markov chain Monte Carlo maximum likelihood, which is a feasible and a useful technique. The proposed method depends on a detrending step built from continuous or categorical explanatory variables, or a mixture among them, by using an appropriate Euclidean distance. The method is illustrated through the analysis of the variation in the prevalence of Loa loa among a sample of village residents in Cameroon, where the explanatory variables included elevation, together with maximum normalised-difference vegetation index and the standard deviation of normalised-difference vegetation index calculated from repeated satellite scans over time. © The Author(s) 2013.

Pathological Left-Handedness: An Explanatory Model.

ERIC Educational Resources Information Center

Satz, Paul

Reported was an explanatory conceptual model for pathological left-handedness (PLH) and related hypotheses, some of which could not be tested empirically due to lack of information. The model was reported to provide an explanation for the relationship between handedness and specific learning disability, and handedness and cerebral dominance for…

Modelling Analysis of Students' Processes of Generating Scientific Explanatory Hypotheses

ERIC Educational Resources Information Center

Park, Jongwon

2006-01-01

It has recently been determined that generating an explanatory hypothesis to explain a discrepant event is important for students' conceptual change. The purpose of this study is to investigate how students' generate new explanatory hypotheses. To achieve this goal, questions are used to identify students prior ideas related to electromagnetic…

Use of real-time monitoring to predict concentrations of select constituents in the Menomonee River drainage basin, Southeast Wisconsin, 2008-9

USGS Publications Warehouse

Baldwin, Austin K.; Graczyk, David J.; Robertson, Dale M.; Saad, David A.; Magruder, Christopher

2012-01-01

The models to estimate chloride concentrations all used specific conductance as the explanatory variable, except for the model for the Little Menomonee River near Freistadt, which used both specific conductance and turbidity as explanatory variables. Adjusted R2 values for the chloride models ranged from 0.74 to 0.97. Models to estimate total suspended solids and total phosphorus used turbidity as the only explanatory variable. Adjusted R2 values ranged from 0.77 to 0.94 for the total suspended solids models and from 0.55 to 0.75 for the total phosphorus models. Models to estimate indicator bacteria used water temperature and turbidity as the explanatory variables, with adjusted R2 values from 0.54 to 0.69 for Escherichia coli bacteria models and from 0.54 to 0.74 for fecal coliform bacteria models. Dissolved oxygen was not used in any of the final models. These models may help managers measure the effects of land-use changes and improvement projects, establish total maximum daily loads, estimate important water-quality indicators such as bacteria concentrations, and enable informed decision making in the future.

Prediction of 222Rn in Danish dwellings using geology and house construction information from central databases.

PubMed

Andersen, Claus E; Raaschou-Nielsen, Ole; Andersen, Helle Primdal; Lind, Morten; Gravesen, Peter; Thomsen, Birthe L; Ulbak, Kaare

2007-01-01

A linear regression model has been developed for the prediction of indoor (222)Rn in Danish houses. The model provides proxy radon concentrations for about 21,000 houses in a Danish case-control study on the possible association between residential radon and childhood cancer (primarily leukaemia). The model was calibrated against radon measurements in 3116 houses. An independent dataset with 788 house measurements was used for model performance assessment. The model includes nine explanatory variables, of which the most important ones are house type and geology. All explanatory variables are available from central databases. The model was fitted to log-transformed radon concentrations and it has an R(2) of 40%. The uncertainty associated with individual predictions of (untransformed) radon concentrations is about a factor of 2.0 (one standard deviation). The comparison with the independent test data shows that the model makes sound predictions and that errors of radon predictions are only weakly correlated with the estimates themselves (R(2) = 10%).

Conflicts Management Model in School: A Mixed Design Study

ERIC Educational Resources Information Center

Dogan, Soner

2016-01-01

The object of this study is to evaluate the reasons for conflicts occurring in school according to perceptions and views of teachers and resolution strategies used for conflicts and to build a model based on the results obtained. In the research, explanatory design including quantitative and qualitative methods has been used. The quantitative part…

Validation of an Evaluation Model for Learning Management Systems

ERIC Educational Resources Information Center

Kim, S. W.; Lee, M. G.

2008-01-01

This study aims to validate a model for evaluating learning management systems (LMS) used in e-learning fields. A survey of 163 e-learning experts, regarding 81 validation items developed through literature review, was used to ascertain the importance of the criteria. A concise list of explanatory constructs, including two principle factors, was…

Army College Fund Cost-Effectiveness Study

DTIC Science & Technology

1990-11-01

Section A.2 presents a theory of enlistment supply to provide a basis for specifying the regression model , The model Is specified in Section A.3, which...Supplementary materials are included in the final four sections. Section A.6 provides annual trends in the regression model variables. Estimates of the model ...millions, A.S. ESTIMATION OF A YOUTH EARNINGS FORECASTING MODEL Civilian pay is an important explanatory variable in the regression model . Previous

Random parameter models for accident prediction on two-lane undivided highways in India.

PubMed

Dinu, R R; Veeraragavan, A

2011-02-01

Generalized linear modeling (GLM), with the assumption of Poisson or negative binomial error structure, has been widely employed in road accident modeling. A number of explanatory variables related to traffic, road geometry, and environment that contribute to accident occurrence have been identified and accident prediction models have been proposed. The accident prediction models reported in literature largely employ the fixed parameter modeling approach, where the magnitude of influence of an explanatory variable is considered to be fixed for any observation in the population. Similar models have been proposed for Indian highways too, which include additional variables representing traffic composition. The mixed traffic on Indian highways comes with a lot of variability within, ranging from difference in vehicle types to variability in driver behavior. This could result in variability in the effect of explanatory variables on accidents across locations. Random parameter models, which can capture some of such variability, are expected to be more appropriate for the Indian situation. The present study is an attempt to employ random parameter modeling for accident prediction on two-lane undivided rural highways in India. Three years of accident history, from nearly 200 km of highway segments, is used to calibrate and validate the models. The results of the analysis suggest that the model coefficients for traffic volume, proportion of cars, motorized two-wheelers and trucks in traffic, and driveway density and horizontal and vertical curvatures are randomly distributed across locations. The paper is concluded with a discussion on modeling results and the limitations of the present study. Copyright © 2010 Elsevier Ltd. All rights reserved.

Dose-Response Calculator for ArcGIS

USGS Publications Warehouse

Hanser, Steven E.; Aldridge, Cameron L.; Leu, Matthias; Nielsen, Scott E.

2011-01-01

The Dose-Response Calculator for ArcGIS is a tool that extends the Environmental Systems Research Institute (ESRI) ArcGIS 10 Desktop application to aid with the visualization of relationships between two raster GIS datasets. A dose-response curve is a line graph commonly used in medical research to examine the effects of different dosage rates of a drug or chemical (for example, carcinogen) on an outcome of interest (for example, cell mutations) (Russell and others, 1982). Dose-response curves have recently been used in ecological studies to examine the influence of an explanatory dose variable (for example, percentage of habitat cover, distance to disturbance) on a predicted response (for example, survival, probability of occurrence, abundance) (Aldridge and others, 2008). These dose curves have been created by calculating the predicted response value from a statistical model at different levels of the explanatory dose variable while holding values of other explanatory variables constant. Curves (plots) developed using the Dose-Response Calculator overcome the need to hold variables constant by using values extracted from the predicted response surface of a spatially explicit statistical model fit in a GIS, which include the variation of all explanatory variables, to visualize the univariate response to the dose variable. Application of the Dose-Response Calculator can be extended beyond the assessment of statistical model predictions and may be used to visualize the relationship between any two raster GIS datasets (see example in tool instructions). This tool generates tabular data for use in further exploration of dose-response relationships and a graph of the dose-response curve.

Explanatory Models for Psychiatric Illness

PubMed Central

Kendler, Kenneth S.

2009-01-01

How can we best develop explanatory models for psychiatric disorders? Because causal factors have an impact on psychiatric illness both at micro levels and macro levels, both within and outside of the individual, and involving processes best understood from biological, psychological, and sociocultural perspectives, traditional models of science that strive for single broadly applicable explanatory laws are ill suited for our field. Such models are based on the incorrect assumption that psychiatric illnesses can be understood from a single perspective. A more appropriate scientific model for psychiatry emphasizes the understanding of mechanisms, an approach that fits naturally with a multicausal framework and provides a realistic paradigm for scientific progress, that is, understanding mechanisms through decomposition and reassembly. Simple subunits of complicated mechanisms can be usefully studied in isolation. Reassembling these constituent parts into a functioning whole, which is straightforward for simple additive mechanisms, will be far more challenging in psychiatry where causal networks contain multiple nonlinear interactions and causal loops. Our field has long struggled with the interrelationship between biological and psychological explanatory perspectives. Building from the seminal work of the neuronal modeler and philosopher David Marr, the author suggests that biology will implement but not replace psychology within our explanatory systems. The iterative process of interactions between biology and psychology needed to achieve this implementation will deepen our understanding of both classes of processes. PMID:18483135

The Development and Application of the Explanatory Model of School Dysfunctions

ERIC Educational Resources Information Center

Bergman, Manfred Max; Bergman, Zinette; Gravett, Sarah

2011-01-01

This article develops the Explanatory Model of School Dysfunctions based on 80 essays of school principals and their representatives in Gauteng. It reveals the degree and kinds of school dysfunctions, as well as their interconnectedness with actors, networks, and domains. The model provides a basis for theory-based analyses of specific…

Explanatory Model for Sound Amplification in a Stethoscope

ERIC Educational Resources Information Center

Eshach, H.; Volfson, A.

2015-01-01

In the present paper we suggest an original physical explanatory model that explains the mechanism of the sound amplification process in a stethoscope. We discuss the amplification of a single pulse, a continuous wave of certain frequency, and finally we address the resonant frequencies. It is our belief that this model may provide students with…

A model for field toxicity tests

USGS Publications Warehouse

Kaiser, Mark S.; Finger, Susan E.

1996-01-01

Toxicity tests conducted under field conditions present an interesting challenge for statistical modelling. In contrast to laboratory tests, the concentrations of potential toxicants are not held constant over the test. In addition, the number and identity of toxicants that belong in a model as explanatory factors are not known and must be determined through a model selection process. We present one model to deal with these needs. This model takes the record of mortalities to form a multinomial distribution in which parameters are modelled as products of conditional daily survival probabilities. These conditional probabilities are in turn modelled as logistic functions of the explanatory factors. The model incorporates lagged values of the explanatory factors to deal with changes in the pattern of mortalities over time. The issue of model selection and assessment is approached through the use of generalized information criteria and power divergence goodness-of-fit tests. These model selection criteria are applied in a cross-validation scheme designed to assess the ability of a model to both fit data used in estimation and predict data deleted from the estimation data set. The example presented demonstrates the need for inclusion of lagged values of the explanatory factors and suggests that penalized likelihood criteria may not provide adequate protection against overparameterized models in model selection.

Using explanatory crop models to develop simple tools for Advanced Life Support system studies

NASA Technical Reports Server (NTRS)

Cavazzoni, J.

2004-01-01

System-level analyses for Advanced Life Support require mathematical models for various processes, such as for biomass production and waste management, which would ideally be integrated into overall system models. Explanatory models (also referred to as mechanistic or process models) would provide the basis for a more robust system model, as these would be based on an understanding of specific processes. However, implementing such models at the system level may not always be practicable because of their complexity. For the area of biomass production, explanatory models were used to generate parameters and multivariable polynomial equations for basic models that are suitable for estimating the direction and magnitude of daily changes in canopy gas-exchange, harvest index, and production scheduling for both nominal and off-nominal growing conditions. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

Older Men's Explanatory Model for Osteoporosis

ERIC Educational Resources Information Center

Solimeo, Samantha L.; Weber, Thomas J.; Gold, Deborah T.

2011-01-01

Purpose: To explore the nature of men's experiences of osteoporosis by developing an understanding of men's explanatory models. Design and Methods: This descriptive study invited community-residing male osteoporosis patients aged 50+ to participate in interviews about osteoporosis. Participants were recruited from a hospital-affiliated bone…

A FORTRAN program for multivariate survival analysis on the personal computer.

PubMed

Mulder, P G

1988-01-01

In this paper a FORTRAN program is presented for multivariate survival or life table regression analysis in a competing risks' situation. The relevant failure rate (for example, a particular disease or mortality rate) is modelled as a log-linear function of a vector of (possibly time-dependent) explanatory variables. The explanatory variables may also include the variable time itself, which is useful for parameterizing piecewise exponential time-to-failure distributions in a Gompertz-like or Weibull-like way as a more efficient alternative to Cox's proportional hazards model. Maximum likelihood estimates of the coefficients of the log-linear relationship are obtained from the iterative Newton-Raphson method. The program runs on a personal computer under DOS; running time is quite acceptable, even for large samples.

Using Qualitative Methods to Explore Lay Explanatory Models, Health-Seeking Behaviours and Self-Care Practices of Podoconiosis Patients in North-West Ethiopia.

PubMed

Banks, Harrison S; Tsegay, Girmay; Wubie, Moges; Tamiru, Abreham; Davey, Gail; Cooper, Max

2016-08-01

Podoconiosis (endemic non-filarial elephantiasis) is a chronic, non-infectious disease resulting from exposure of bare feet to red-clay soil in tropical highlands. This study examined lay beliefs about three under-researched aspects of podoconiosis patients' care: explanatory models, health-seeking behaviours and self-care. In-depth interviews and focus group discussions were undertaken with 34 participants (19 male, 15 female) between April-May 2015 at podoconiosis treatment centres across East and West Gojjam regions in north-west Ethiopia. Explanatory models for podoconiosis included contamination from blood, magic, soil or affected individuals. Belief in heredity or divine punishment often delayed clinic attendance. All participants had tried holy water treatment and some, holy soil. Herbal treatments were considered ineffectual, costly and appeared to promote fluid escape. Motivators for clinic attendance were failure of traditional treatments and severe or disabling symptoms. Patients did not report self-treatment with antibiotics. Self-care was hindered by water being unavailable or expensive and patient fatigue. A pluralistic approach to podoconiosis self-treatment was discovered. Holy water is widely valued, though some patients prefer holy soil. Priests and traditional healers could help promote self-care and "signpost" patients to clinics. Change in behaviour and improving water access is key to self-care.

The Role of Scientific Modeling Criteria in Advancing Students' Explanatory Ideas of Magnetism

ERIC Educational Resources Information Center

Cheng, Meng-Fei; Brown, David E.

2015-01-01

Student construction of models is a strong focus of current research and practice in science education. In order to study in detail the interactions between students' model generation and evaluation and their development of explanatory ideas to account for magnetic phenomena, a multi-session teaching experiment was conducted with a small number of…

Evaluation of alternative model selection criteria in the analysis of unimodal response curves using CART

USGS Publications Warehouse

Ribic, C.A.; Miller, T.W.

1998-01-01

We investigated CART performance with a unimodal response curve for one continuous response and four continuous explanatory variables, where two variables were important (ie directly related to the response) and the other two were not. We explored performance under three relationship strengths and two explanatory variable conditions: equal importance and one variable four times as important as the other. We compared CART variable selection performance using three tree-selection rules ('minimum risk', 'minimum risk complexity', 'one standard error') to stepwise polynomial ordinary least squares (OLS) under four sample size conditions. The one-standard-error and minimum-risk-complexity methods performed about as well as stepwise OLS with large sample sizes when the relationship was strong. With weaker relationships, equally important explanatory variables and larger sample sizes, the one-standard-error and minimum-risk-complexity rules performed better than stepwise OLS. With weaker relationships and explanatory variables of unequal importance, tree-structured methods did not perform as well as stepwise OLS. Comparing performance within tree-structured methods, with a strong relationship and equally important explanatory variables, the one-standard-error-rule was more likely to choose the correct model than were the other tree-selection rules 1) with weaker relationships and equally important explanatory variables; and 2) under all relationship strengths when explanatory variables were of unequal importance and sample sizes were lower.

Temporal Trends and Hydrological Controls of Fisheries Production in the Madeira River (Brazil)

NASA Astrophysics Data System (ADS)

Kaplan, D. A.; Lima, M. A.; Doria, C.

2016-12-01

Amazonian river systems are characterized by a strongly seasonal flood pulse and important hydrologic effects have been observed in the dynamics of fish stocks and fishing yields. Changes in the Amazon's freshwater ecosystems from hydropower development will have a cascade of physical, ecological, and social effects and impacts on fish and fisheries are expected to be potentially irreversible. In this work we investigate shared trends and causal factors driving fish catch in the Madeira River (a major tributary of the Amazon) before dam construction to derive relationships between catch and natural hydrologic dynamics. We applied Dynamic Factor Analysis to investigate dynamics in fish catch across ten commercially important fish species in the Madeira River using daily fish landings data including species and total weight and daily hydrological data obtained from the Brazilian Geological Service. Total annual catch averaged over the 18-yr period (1990-2007) was 849 tons yr-1. Species with the highest catch included curimatã, dourada/filhote and pacu, highlighting the importance of medium and long-distance migratory species for fisheries production. We found a four-trend dynamic factor model (DFM) to best fit the observed data, assessed using the Akaike Information Criteria. Model goodness of fit was fair (R2=0.51) but highly variable across species (0.16 ≤ R2 ≤ 0.95). Fitted trends exhibited strong and regular year-to-year variation representative of the seasonal hydrologic pulsing observed on the Madeira River. Next, we considered 11 candidate explanatory time series and found the best DFM used four explanatory variables and only one common trend. While the model fit with explanatory variables was lower (R2=0.31) it removed much reliance on unknown common trends. The most important explanatory variable in this model was maximum water level followed by days flooded, river flow of the previous year and increment. We found unique responses to hydrological variations across the ten species, suggesting that dam operating rules need to closely mimic natural hydrologic regime in order to maintain the dynamics of these ecosystems. Future multidisciplinary analyses to understand the complex social-ecological effects of dams are needed to improve management practices and support sustainable livelihoods.

Explanatory Models of Illness: A Study of Within-Culture Variation

ERIC Educational Resources Information Center

Lynch, Elizabeth; Medin, Douglas

2006-01-01

The current studies explore causal models of heart attack and depression generated from American healers whom use distinct explanatory frameworks. Causal chains leading to two illnesses, heart attack and depression, were elicited from participant groups: registered nurses (RNs), energy healers, RN energy healers, and undergraduates. The…

Combined Effects of Soil Biotic and Abiotic Factors, Influenced by Sewage Sludge Incorporation, on the Incidence of Corn Stalk Rot

PubMed Central

Fortes, Nara Lúcia Perondi; Navas-Cortés, Juan A; Silva, Carlos Alberto; Bettiol, Wagner

2016-01-01

The objectives of this study were to evaluate the combined effects of soil biotic and abiotic factors on the incidence of Fusarium corn stalk rot, during four annual incorporations of two types of sewage sludge into soil in a 5-years field assay under tropical conditions and to predict the effects of these variables on the disease. For each type of sewage sludge, the following treatments were included: control with mineral fertilization recommended for corn; control without fertilization; sewage sludge based on the nitrogen concentration that provided the same amount of nitrogen as in the mineral fertilizer treatment; and sewage sludge that provided two, four and eight times the nitrogen concentration recommended for corn. Increasing dosages of both types of sewage sludge incorporated into soil resulted in increased corn stalk rot incidence, being negatively correlated with corn yield. A global analysis highlighted the effect of the year of the experiment, followed by the sewage sludge dosages. The type of sewage sludge did not affect the disease incidence. A multiple logistic model using a stepwise procedure was fitted based on the selection of a model that included the three explanatory parameters for disease incidence: electrical conductivity, magnesium and Fusarium population. In the selected model, the probability of higher disease incidence increased with an increase of these three explanatory parameters. When the explanatory parameters were compared, electrical conductivity presented a dominant effect and was the main variable to predict the probability distribution curves of Fusarium corn stalk rot, after sewage sludge application into the soil. PMID:27176597

Public Views on the Gendering of Mathematics and Related Careers: International Comparisons

ERIC Educational Resources Information Center

Forgasz, Helen; Leder, Gilah; Tan, Hazel

2014-01-01

Mathematics continues to be an enabling discipline for Science, Technology, Engineering, and Mathematics (STEM)-based university studies and related careers. Explanatory models for females' underrepresentation in higher level mathematics and STEM-based courses comprise learner-related and environmental variables--including societal beliefs. Using…

Parental Explanatory Models of Child's Intellectual Disability: A Q Methodology Study

ERIC Educational Resources Information Center

John, Aesha; Montgomery, Diane

2016-01-01

This study with families caring for an individual with an intellectual disability in a mid-sized Indian city explored the diverse explanatory models that parents constructed of causes, preferred treatment approaches and perceived social effects of their child's intellectual disability. Seventeen mothers and three fathers rank ordered 48 disability…

Predictive and Explanatory Relationship Model between Procrastination, Motivation, Anxiety and Academic Achievement

ERIC Educational Resources Information Center

Akpur, Ugur

2017-01-01

Purpose: The purpose of this study is to determine the predictive and explanatory relationship model between procrastination, motivation, anxiety and academic achievement of university students. Research Methods: In this study, a causal research design was used. The study group consisted of 211 participants. In order to determine their motivation…

The psychological factor 'self-blame' predicts overuse injury among top-level Swedish track and field athletes: a 12-month cohort study.

PubMed

Timpka, Toomas; Jacobsson, Jenny; Dahlström, Örjan; Kowalski, Jan; Bargoria, Victor; Ekberg, Joakim; Nilsson, Sverker; Renström, Per

2015-11-01

Athletes' psychological characteristics are important for understanding sports injury mechanisms. We examined the relevance of psychological factors in an integrated model of overuse injury risk in athletics/track and field. Swedish track and field athletes (n=278) entering a 12-month injury surveillance in March 2009 were also invited to complete a psychological survey. Simple Cox proportional hazards models were compiled for single explanatory variables. We also tested multiple models for 3 explanatory variable groupings: an epidemiological model without psychological variables, a psychological model excluding epidemiological variables and an integrated (combined) model. The integrated multiple model included the maladaptive coping behaviour self-blame (p=0.007; HR 1.32; 95% CI 1.08 to 1.61), and an interaction between athlete category and injury history (p<0.001). Youth female (p=0.034; HR 0.51; 95% CI 0.27 to 0.95) and youth male (p=0.047; HR 0.49; 95% CI 0.24 to 0.99) athletes with no severe injury the previous year were at half the risk of sustaining a new injury compared with the reference group. A training load index entered the epidemiological multiple model, but not the integrated model. The coping behaviour self-blame replaced training load in an integrated explanatory model of overuse injury risk in athletes. What seemed to be more strongly related to the likelihood of overuse injury was not the athletics load per se, but, rather, the load applied in situations when the athlete's body was in need of rest. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Temporal self-regulation theory: a neurobiologically informed model for physical activity behavior

PubMed Central

Hall, Peter A.; Fong, Geoffrey T.

2015-01-01

Dominant explanatory models for physical activity behavior are limited by the exclusion of several important components, including temporal dynamics, ecological forces, and neurobiological factors. The latter may be a critical omission, given the relevance of several aspects of cognitive function for the self-regulatory processes that are likely required for consistent implementation of physical activity behavior in everyday life. This narrative review introduces temporal self-regulation theory (TST; Hall and Fong, 2007, 2013) as a new explanatory model for physical activity behavior. Important features of the model include consideration of the default status of the physical activity behavior, as well as the disproportionate influence of temporally proximal behavioral contingencies. Most importantly, the TST model proposes positive feedback loops linking executive function (EF) and the performance of physical activity behavior. Specifically, those with relatively stronger executive control (and optimized brain structures supporting it, such as the dorsolateral prefrontal cortex (PFC)) are able to implement physical activity with more consistency than others, which in turn serves to strengthen the executive control network itself. The TST model has the potential to explain everyday variants of incidental physical activity, sport-related excellence via capacity for deliberate practice, and variability in the propensity to schedule and implement exercise routines. PMID:25859196

Explanatory models of adult patients with type 2 diabetes mellitus from urban centers of central Ethiopia.

PubMed

Habte, Bruck M; Kebede, Tedla; Fenta, Teferi G; Boon, Heather

2016-09-13

Type 2 diabetes, which is increasing as a public health problem in the low resource settings of Africa has been associated with the high prevalence of micro-vascular complications and increasing levels of macro-vascular complications. There is evidence from the developed world that understanding patient perceptions of chronic illness is important to design effective strategies for helping patients manage these conditions. This study utilized Kleinman's model to explore the illness perceptions of type 2 diabetes patients attending treatment in Addis Ababa and Butajira (Ethiopia) and better understand how they manage their illness. Qualitative interviews were conducted to elicit the explanatory models of purposively sampled type 2 diabetes patients attending treatment in three hospitals in central Ethiopia until saturation of key emerging themes was achieved. Analysis of interview transcripts was guided by Kleinman's model. A total of 39 participants, 24 from Addis Ababa and the rest from Butajira took part in the study. This study revealed that patients' explanatory models were informed by both the traditional and biomedical models with emotional distress evident in some of the participants. The traditional model seemed to reflect the strong religious and cultural influences for the majority of study participants. The findings also revealed that symptoms played significant roles in how patients viewed their illness including assessment of its severity. Most were uncertain about the cause of their illness, with those expressing certainty citing factors over which they believed they had little or no control. This may have contributed to the perceptions about the use of religious healing and traditional medicines in a complementary or alternative manner to the biomedical regimen which could affect their adherence to recommended regimens and their health outcomes. This study suggests the need for a strong diabetes care program that is sensitive to patients' experiences of their illness including emotional distress. Individuals providing the diabetes care should consider local and individual contexts and strive to make their approach patient-centered and engage active participation of patients. There appears to be a need for better training of health providers in different areas including health communications and the fundamentals of mental healthcare.

Explanation in Biology: Reduction, Pluralism, and Explanatory Aims

ERIC Educational Resources Information Center

Brigandt, Ingo

2013-01-01

This essay analyzes and develops recent views about explanation in biology. Philosophers of biology have parted with the received deductive-nomological model of scientific explanation primarily by attempting to capture actual biological theorizing and practice. This includes an endorsement of different kinds of explanation (e.g., mathematical and…

Constructing and De-Constructing Cultural Values: An Explanatory Model of Teaching Behaviours.

ERIC Educational Resources Information Center

Boufoy-Bastick, Beatrice

This paper presents an explanatory model of cultural behaviors, which resulted from a 4-year ethnographic study of the different academic attainments in English of indigenous Fijians and the Indo-Fijians in the Fiji Islands. Fiji is a natural laboratory for investigating differential cultural behaviors because of these two culturally distinct main…

Parents' and Speech and Language Therapists' Explanatory Models of Language Development, Language Delay and Intervention

ERIC Educational Resources Information Center

Marshall, Julie; Goldbart, Juliet; Phillips, Julie

2007-01-01

Background: Parental and speech and language therapist (SLT) explanatory models may affect engagement with speech and language therapy, but there has been dearth of research in this area. This study investigated parents' and SLTs' views about language development, delay and intervention in pre-school children with language delay. Aims: The aims…

Why Do Adolescents Use Drugs? A Common Sense Explanatory Model from the Social Actor's Perspective

ERIC Educational Resources Information Center

Nuno-Gutierrez, Bertha Lidia; Rodriguez-Cerda, Oscar; Alvarez-Nemegyei, Jose

2006-01-01

Analysis was made of the common sense explanations of 60 Mexican teenage illicit drug users in rehabilitation to determine their drug use debut. The explanatory model was separated into three blocks, two of which contained common sense aspects: interaction between subject's plane and the collectivity; and relationship between subject's interior…

Divergent Explanatory Production (DEP): The Relationship between Resilience and Creativity

ERIC Educational Resources Information Center

Hernández, Óscar Sánchez; Méndez, Francisco Xavier; Garber, Judy

2015-01-01

Introduction: The aim of the study is to describe and analyze a new test and construct, Divergent Explanatory Production (DEP), defined as the ability to observe adverse situations from various points of view. At the theoretical level, it is a bridge between the reformulated model of learned helplessness (as a resilience model), and creative…

Using Qualitative Methods to Explore Lay Explanatory Models, Health-Seeking Behaviours and Self-Care Practices of Podoconiosis Patients in North-West Ethiopia

PubMed Central

Banks, Harrison S.; Tsegay, Girmay; Wubie, Moges; Tamiru, Abreham; Davey, Gail; Cooper, Max

2016-01-01

Background Podoconiosis (endemic non-filarial elephantiasis) is a chronic, non-infectious disease resulting from exposure of bare feet to red-clay soil in tropical highlands. This study examined lay beliefs about three under-researched aspects of podoconiosis patients’ care: explanatory models, health-seeking behaviours and self-care. Methods In-depth interviews and focus group discussions were undertaken with 34 participants (19 male, 15 female) between April-May 2015 at podoconiosis treatment centres across East and West Gojjam regions in north-west Ethiopia. Results Explanatory models for podoconiosis included contamination from blood, magic, soil or affected individuals. Belief in heredity or divine punishment often delayed clinic attendance. All participants had tried holy water treatment and some, holy soil. Herbal treatments were considered ineffectual, costly and appeared to promote fluid escape. Motivators for clinic attendance were failure of traditional treatments and severe or disabling symptoms. Patients did not report self-treatment with antibiotics. Self-care was hindered by water being unavailable or expensive and patient fatigue. Conclusion A pluralistic approach to podoconiosis self-treatment was discovered. Holy water is widely valued, though some patients prefer holy soil. Priests and traditional healers could help promote self-care and “signpost” patients to clinics. Change in behaviour and improving water access is key to self-care. PMID:27536772

Azúcar y nervios: explanatory models and treatment experiences of Hispanics with diabetes and depression.

PubMed

Cabassa, Leopoldo J; Hansen, Marissa C; Palinkas, Lawrence A; Ell, Kathleen

2008-06-01

This study examined the explanatory models of depression, perceived relationships between diabetes and depression, and depression treatment experiences of low-income, Spanish-speaking, Hispanics with diabetes and depression. A purposive sample (n=19) was selected from participants enrolled in a randomized controlled trial conducted in Los Angeles, California (United States) testing the effectiveness of a health services quality improvement intervention. Four focus groups followed by 10 in-depth semi-structured qualitative interviews were conducted. Data were analyzed using the methodology of coding, consensus, co-occurrence, and comparison, an analytical strategy rooted in grounded theory. Depression was perceived as a serious condition linked to the accumulation of social stressors. Somatic and anxiety-like symptoms and the cultural idiom of nervios were central themes in low-income Hispanics' explanatory models of depression. The perceived reciprocal relationships between diabetes and depression highlighted the multiple pathways by which these two illnesses impact each other and support the integration of diabetes and depression treatments. Concerns about depression treatments included fears about the addictive and harmful properties of antidepressants, worries about taking too many pills, and the stigma attached to taking psychotropic medications. This study provides important insights about the cultural and social dynamics that shape low-income Hispanics' illness and treatment experiences and support the use of patient-centered approaches to reduce the morbidity and mortality associated with diabetes and depression.

“Azúcar y Nervios: Explanatory Models and Treatment Experiences of Hispanics with Diabetes and Depression”

PubMed Central

Hansen, Marissa C; Palinkas, Lawrence A; Ell, Kathleen

2008-01-01

This study examined the explanatory models of depression, perceived relationships between diabetes and depression, and depression treatment experiences of low-income, Spanish-speaking, Hispanics with diabetes and depression. A purposive sample (n =19) was selected from participants enrolled in a randomized controlled trial conducted in Los Angeles, California (US) testing the effectiveness of a health services quality improvement intervention. Four focus groups followed by 10 in-depth semi-structured qualitative interviews were conducted. Data were analyzed using the methodology of coding, consensus, co-occurrence, and comparison, an analytical strategy rooted in grounded theory. Depression was perceived as a serious condition linked to the accumulation of social stressors. Somatic and anxiety-like symptoms and the cultural idiom of nervios were central themes in low-income Hispanics’ explanatory models of depression. The perceived reciprocal relationships between diabetes and depression highlighted the multiple pathways by which these two illnesses impact each other and support the integration of diabetes and depression treatments. Concerns about depression treatments included fears about the addictive and harmful properties of antidepressants, worries about taking too many pills, and the stigma attached to taking psychotropic medications. This study provides important insights about the cultural and social dynamics that shape low-income Hispanics’ illness and treatment experiences and support the use of patient-centered approaches to reduce the morbidity and mortality associated with diabetes and depression. PMID:18339466

The effect of topography on arctic-alpine aboveground biomass and NDVI patterns

NASA Astrophysics Data System (ADS)

Riihimäki, Henri; Heiskanen, Janne; Luoto, Miska

2017-04-01

Topography is a key factor affecting numerous environmental phenomena, including Arctic and alpine aboveground biomass (AGB) distribution. Digital Elevation Model (DEM) is a source of topographic information which can be linked to local growing conditions. Here, we investigated the effect of DEM derived variables, namely elevation, topographic position, radiation and wetness on AGB and Normalized Difference Vegetation Index (NDVI) in a Fennoscandian forest-alpine tundra ecotone. Boosted regression trees were used to derive non-parametric response curves and relative influences of the explanatory variables. Elevation and potential incoming solar radiation were the most important explanatory variables for both AGB and NDVI. In the NDVI models, the response curves were smooth compared with AGB models. This might be caused by large contribution of field and shrub layer to NDVI, especially at the treeline. Furthermore, radiation and elevation had a significant interaction, showing that the highest NDVI and biomass values are found from low-elevation, high-radiation sites, typically on the south-southwest facing valley slopes. Topographic wetness had minor influence on AGB and NDVI. Topographic position had generally weak effects on AGB and NDVI, although protected topographic position seemed to be more favorable below the treeline. The explanatory power of the topographic variables, particularly elevation and radiation demonstrates that DEM-derived land surface parameters can be used for exploring biomass distribution resulting from landform control on local growing conditions.

Refinement of regression models to estimate real-time concentrations of contaminants in the Menomonee River drainage basin, southeast Wisconsin, 2008-11

USGS Publications Warehouse

Baldwin, Austin K.; Robertson, Dale M.; Saad, David A.; Magruder, Christopher

2013-01-01

In 2008, the U.S. Geological Survey and the Milwaukee Metropolitan Sewerage District initiated a study to develop regression models to estimate real-time concentrations and loads of chloride, suspended solids, phosphorus, and bacteria in streams near Milwaukee, Wisconsin. To collect monitoring data for calibration of models, water-quality sensors and automated samplers were installed at six sites in the Menomonee River drainage basin. The sensors continuously measured four potential explanatory variables: water temperature, specific conductance, dissolved oxygen, and turbidity. Discrete water-quality samples were collected and analyzed for five response variables: chloride, total suspended solids, total phosphorus, Escherichia coli bacteria, and fecal coliform bacteria. Using the first year of data, regression models were developed to continuously estimate the response variables on the basis of the continuously measured explanatory variables. Those models were published in a previous report. In this report, those models are refined using 2 years of additional data, and the relative improvement in model predictability is discussed. In addition, a set of regression models is presented for a new site in the Menomonee River Basin, Underwood Creek at Wauwatosa. The refined models use the same explanatory variables as the original models. The chloride models all used specific conductance as the explanatory variable, except for the model for the Little Menomonee River near Freistadt, which used both specific conductance and turbidity. Total suspended solids and total phosphorus models used turbidity as the only explanatory variable, and bacteria models used water temperature and turbidity as explanatory variables. An analysis of covariance (ANCOVA), used to compare the coefficients in the original models to those in the refined models calibrated using all of the data, showed that only 3 of the 25 original models changed significantly. Root-mean-squared errors (RMSEs) calculated for both the original and refined models using the entire dataset showed a median improvement in RMSE of 2.1 percent, with a range of 0.0–13.9 percent. Therefore most of the original models did almost as well at estimating concentrations during the validation period (October 2009–September 2011) as the refined models, which were calibrated using those data. Application of these refined models can produce continuously estimated concentrations of chloride, total suspended solids, total phosphorus, E. coli bacteria, and fecal coliform bacteria that may assist managers in quantifying the effects of land-use changes and improvement projects, establish total maximum daily loads, and enable better informed decision making in the future.

'Food Sticking in My Throat': Videofluoroscopic Evaluation of a Common Symptom.

PubMed

Madhavan, Aarthi; Carnaby, Giselle D; Crary, Michael A

2015-06-01

Prevalence of the symptom of food 'sticking' during swallowing has been reported to range from 5 to 50%, depending on the assessment setting. However, limited objective evidence has emerged to clarify factors that contribute to this symptom. Three hundred and fifteen patient records from an outpatient dysphagia clinic were reviewed to identify patients with symptoms of 'food sticking in the throat.' Corresponding videofluoroscopic swallowing studies for patients with this complaint were reviewed for the following variables: accuracy of symptom localization, identification and characteristics (anatomic, physiologic) of an explanatory cause for the symptom, and the specific swallowed material that identified the explanatory cause. One hundred and forty one patients (45%) were identified with a complaint of food 'sticking' in their throat during swallowing. Prevalence of explanatory findings on fluoroscopy was 76% (107/141). Eighty five percent (91/107) of explanatory causes were physiologic in nature, while 15% (16/107) were anatomic. The majority of explanatory causes were identified in the esophagus (71%). Symptom localization was more accurate when the explanatory cause was anatomic versus physiologic (75 vs. 18%). A non-masticated marshmallow presented with the highest diagnostic yield in identification of explanatory causes (71%). Patients complaining of 'food sticking in the throat' are likely to present with esophageal irregularities. Thus, imaging studies of swallowing function should include the esophagus. A range of materials, including a non-masticated marshmallow, is helpful in determining the location and characteristics of swallowing deficits contributing to this symptom.

Why the Difference Between Explanation and Argument Matters to Science Education

NASA Astrophysics Data System (ADS)

Brigandt, Ingo

2016-05-01

Contributing to the recent debate on whether or not explanations ought to be differentiated from arguments, this article argues that the distinction matters to science education. I articulate the distinction in terms of explanations and arguments having to meet different standards of adequacy. Standards of explanatory adequacy are important because they correspond to what counts as a good explanation in a science classroom, whereas a focus on evidence-based argumentation can obscure such standards of what makes an explanation explanatory. I provide further reasons for the relevance of not conflating explanations with arguments (and having standards of explanatory adequacy in view). First, what guides the adoption of the particular standards of explanatory adequacy that are relevant in a scientific case is the explanatory aim pursued in this context. Apart from explanatory aims being an important aspect of the nature of science, including explanatory aims in classroom instruction also promotes students seeing explanations as more than facts, and engages them in developing explanations as responses to interesting explanatory problems. Second, it is of relevance to science curricula that science aims at intervening in natural processes, not only for technological applications, but also as part of experimental discovery. Not any argument enables intervention in nature, as successful intervention specifically presupposes causal explanations. Students can fruitfully explore in the classroom how an explanatory account suggests different options for intervention.

Development and Application of Regression Models for Estimating Nutrient Concentrations in Streams of the Conterminous United States, 1992-2001

USGS Publications Warehouse

Spahr, Norman E.; Mueller, David K.; Wolock, David M.; Hitt, Kerie J.; Gronberg, JoAnn M.

2010-01-01

Data collected for the U.S. Geological Survey National Water-Quality Assessment program from 1992-2001 were used to investigate the relations between nutrient concentrations and nutrient sources, hydrology, and basin characteristics. Regression models were developed to estimate annual flow-weighted concentrations of total nitrogen and total phosphorus using explanatory variables derived from currently available national ancillary data. Different total-nitrogen regression models were used for agricultural (25 percent or more of basin area classified as agricultural land use) and nonagricultural basins. Atmospheric, fertilizer, and manure inputs of nitrogen, percent sand in soil, subsurface drainage, overland flow, mean annual precipitation, and percent undeveloped area were significant variables in the agricultural basin total nitrogen model. Significant explanatory variables in the nonagricultural total nitrogen model were total nonpoint-source nitrogen input (sum of nitrogen from manure, fertilizer, and atmospheric deposition), population density, mean annual runoff, and percent base flow. The concentrations of nutrients derived from regression (CONDOR) models were applied to drainage basins associated with the U.S. Environmental Protection Agency (USEPA) River Reach File (RF1) to predict flow-weighted mean annual total nitrogen concentrations for the conterminous United States. The majority of stream miles in the Nation have predicted concentrations less than 5 milligrams per liter. Concentrations greater than 5 milligrams per liter were predicted for a broad area extending from Ohio to eastern Nebraska, areas spatially associated with greater application of fertilizer and manure. Probabilities that mean annual total-nitrogen concentrations exceed the USEPA regional nutrient criteria were determined by incorporating model prediction uncertainty. In all nutrient regions where criteria have been established, there is at least a 50 percent probability of exceeding the criteria in more than half of the stream miles. Dividing calibration sites into agricultural and nonagricultural groups did not improve the explanatory capability for total phosphorus models. The group of explanatory variables that yielded the lowest model error for mean annual total phosphorus concentrations includes phosphorus input from manure, population density, amounts of range land and forest land, percent sand in soil, and percent base flow. However, the large unexplained variability and associated model error precluded the use of the total phosphorus model for nationwide extrapolations.

Analysis of the Explanatory Variables of the Differences in Perceptions of Cyberbullying: A Role-Based-Model Approach.

PubMed

Fernández-Antelo, Inmaculada; Cuadrado-Gordillo, Isabel

2018-04-01

The controversies that exist regarding the delimitation of the cyberbullying construct demonstrate the need for further research focused on determining the criteria that shape the structure of the perceptions that adolescents have of this phenomenon and on seeking explanations of this behavior. The objectives of this study were to (a) construct possible explanatory models of the perception of cyberbullying from identifying and relating the criteria that form this construct and (b) analyze the influence of previous cyber victimization and cyber aggression experiences in the construction of explanatory models of the perception of cyberbullying. The sample consisted of 2,148 adolescents (49.1% girls; SD = 0.5) aged from 12 to 16 years ( M = 13.9 years; SD = 1.2). The results have shown that previous cyber victimization and cyber aggression experiences lead to major differences in the explanatory models to interpret cyber-abusive behavior as cyberbullying episodes, or as social relationship mechanisms, or as a revenge reaction. We note that the aggressors' explanatory model is based primarily on a strong reciprocal relationship between the imbalance of power and intentionality, that it functions as a link promoting indirect causal relationships of the anonymity and repetition factors with the cyberbullying construct. The victims' perceptual structure is based on three criteria-imbalance of power, intentionality, and publicity-where the key factor in this structure is the intention to harm. These results allow to design more effective measures of prevention and intervention closely tailored to addressing directly the factors that are considered to be predictors of risk.

Explanatory models of addictive behaviour among native German, Russian-German, and Turkish youth.

PubMed

Penka, S; Heimann, H; Heinz, A; Schouler-Ocak, M

2008-01-01

In Germany, the public system of addiction treatment is used less by migrants with addictive disorders than by their non-migrant counterparts. To date, the literature has focused primarily on language, sociocultural factors, and residence status when discussing access barriers to this part of the health care system. However, little attention has been paid to cultural differences in explanatory models of addictive behaviour. This is surprising when we consider the important role played by popular knowledge in a population's perceptions of and responses to illnesses, including their causes, symptoms, and treatment. In the present study, we examined explanatory models of addictive behaviour and of mental disorders in 124 native German und Russian-German youth and compared these models to those observed in an earlier study of 144 German and Turkish youth. We employed the free listing technique German and to compile the terms that participating subjects used to describe addictive behaviour. Subsequently, we examined how a subset of our study population assigned these terms to the respective disorders by means of the pile sort method. Although the explanatory models used by the German and Russian-German youth in our study were surprisingly similar, those employed by Turkish youth did not make any fundamental distinction between illegal and legal drugs (e.g. alcohol and nicotine). German and Russian-German youth regarded eating disorders as "embarrassing" or "disgraceful", but Turkish youth did not. Unlike our German and Russian-German subjects, the Turkish youth did not classify eating disorders as being addictive in nature. Moreover, medical concepts crucial to a proper understanding of dependence disorders (e.g. the term "physical dependence") were characterised by almost half of our Turkish subjects as useless in describing addictions. These findings show that it is impossible to translate medical or everyday concepts of disease and treatment properly into a different language without considering the connotations and implications of each term as it relates to the respective culture. Terms that are central to Western medical models of disease may otherwise be misunderstood, misinterpreted, or simply rejected.

Parental Depressive Symptoms and Adolescent Adjustment: A Prospective Test of an Explanatory Model for the Role of Marital Conflict

PubMed Central

Cummings, E. Mark; Cheung, Rebecca Y. M.; Koss, Kalsea; Davies, Patrick T.

2014-01-01

Despite calls for process-oriented models for child maladjustment due to heightened marital conflict in the context of parental depressive symptoms, few longitudinal tests of the mechanisms underlying these relations have been conducted. Addressing this gap, the present study examined multiple factors longitudinally that link parental depressive symptoms to adolescent adjustment problems, building on a conceptual model informed by emotional security theory (EST). Participants were 320 families (158 boys, 162 girls), including mothers and fathers, who took part when their children were in kindergarten (T1), second (T2), seventh (T3), eighth (T4) and ninth (T5) grades. Parental depressive symptoms (T1) were related to changes in adolescents’ externalizing and internalizing symptoms (T5), as mediated by parents’ negative emotional expressiveness (T2), marital conflict (T3), and emotional insecurity (T4). Evidence was thus advanced for emotional insecurity as an explanatory process in the context of parental depressive symptoms. PMID:24652484

Emerging paradigms in medicine: implications for the future of psychiatry.

PubMed

Lake, James

2007-01-01

The causes of mental illness remain obscure in spite of rapid progress in the neurosciences. This is due in part to the fact that contemporary biomedical psychiatry rests on philosophically and scientifically ambiguous ground. In Western medicine paradigms, theories from physics, chemistry, and biology form the basis of an explanatory model of illness, including mental illness. Symptoms are conceptualized as subjective descriptions of effects caused by factors characterized in empirical terms. Conventional biomedicine asserts that all causes of illness, and by extension, mechanisms of action underlying legitimate treatment approaches, rest on biological processes that can be described in the reductionist language of Western science. However, in contemporary Western psychiatry, there is no single adequate explanatory model of the causes of mental illness. What remains are competing psychodynamic, genetic, endocrinologic, and neurobiological models of symptom formation reflecting disparate ideological positions and diverse clinical training backgrounds of mental health professionals. There is no unifying theory in psychiatry because no single explanatory model has been confirmed as more valid than any other. I hypothesize in this article that the synthesis of ideas and clinical approaches from Western biomedicine and non-Western systems of medicine based on understandings of human consciousness, the neurosciences, complexity theory, and quantum field theory, will lead to rapid evolution of conventional Western biomedical psychiatry toward truly integrative mental healthcare. The result will be the emergence of an integrative mental healthcare model that will more adequately address the disparate causes, conditions, and meanings of symptoms combining multimodal approaches from Western biomedicine and non-Western systems of medicine.

'Individualism-collectivism' as an explanatory device for mental illness stigma.

PubMed

Papadopoulos, Chris; Foster, John; Caldwell, Kay

2013-06-01

The aim of this study is investigate whether the cross-cultural value paradigm 'individualism-collectivism' is a useful explanatory model for mental illness stigma on a cultural level. Using snowball sampling, a quantitative questionnaire survey of 305 individuals from four UK-based cultural groups (white-English, American, Greek/Greek Cypriot, and Chinese) was carried out. The questionnaire included the 'Community Attitudes to Mental Illness scale' and the 'vertical-horizontal individualism-collectivism scale'. The results revealed that the more stigmatizing a culture's mental illness attitudes are, the more likely collectivism effectively explains these attitudes. In contrast, the more positive a culture's mental illness attitudes, the more likely individualism effectively explains attitudes. We conclude that a consideration of the individualism-collectivism paradigm should be included in any future research aiming to provide a holistic understanding of the causes of mental illness stigma, particularly when the cultures stigmatization levels are particularly high or low.

Sharpening method of satellite thermal image based on the geographical statistical model

NASA Astrophysics Data System (ADS)

Qi, Pengcheng; Hu, Shixiong; Zhang, Haijun; Guo, Guangmeng

2016-04-01

To improve the effectiveness of thermal sharpening in mountainous regions, paying more attention to the laws of land surface energy balance, a thermal sharpening method based on the geographical statistical model (GSM) is proposed. Explanatory variables were selected from the processes of land surface energy budget and thermal infrared electromagnetic radiation transmission, then high spatial resolution (57 m) raster layers were generated for these variables through spatially simulating or using other raster data as proxies. Based on this, the local adaptation statistical relationship between brightness temperature (BT) and the explanatory variables, i.e., the GSM, was built at 1026-m resolution using the method of multivariate adaptive regression splines. Finally, the GSM was applied to the high-resolution (57-m) explanatory variables; thus, the high-resolution (57-m) BT image was obtained. This method produced a sharpening result with low error and good visual effect. The method can avoid the blind choice of explanatory variables and remove the dependence on synchronous imagery at visible and near-infrared bands. The influences of the explanatory variable combination, sampling method, and the residual error correction on sharpening results were analyzed deliberately, and their influence mechanisms are reported herein.

Explanatory models concerning the effects of small-area characteristics on individual health.

PubMed

Voigtländer, Sven; Vogt, Verena; Mielck, Andreas; Razum, Oliver

2014-06-01

Material and social living conditions at the small-area level are assumed to have an effect on individual health. We review existing explanatory models concerning the effects of small-area characteristics on health and describe the gaps future research should try to fill. Systematic literature search for, and analysis of, studies that propose an explanatory model of the relationship between small-area characteristics and health. Fourteen studies met our inclusion criteria. Using various theoretical approaches, almost all of the models are based on a three-tier structure linking social inequalities (posited at the macro-level), small-area characteristics (posited at the meso-level) and individual health (micro-level). No study explicitly defines the geographical borders of the small-area context. The health impact of the small-area characteristics is explained by specific pathways involving mediating factors (psychological, behavioural, biological). These pathways tend to be seen as uni-directional; often, causality is implied. They may be modified by individual factors. A number of issues need more attention in research on explanatory models concerning small-area effects on health. Among them are the (geographical) definition of the small-area context; the systematic description of pathways comprising small-area contextual as well as compositional factors; questions of direction of association and causality; and the integration of a time dimension.

Mental health assessment: Inference, explanation, and coherence.

PubMed

Thagard, Paul; Larocque, Laurette

2018-06-01

Mental health professionals such as psychiatrists and psychotherapists assess their patients by identifying disorders that explain their symptoms. This assessment requires an inference to the best explanation that compares different disorders with respect to how well they explain the available evidence. Such comparisons are captured by the theory of explanatory coherence that states 7 principles for evaluating competing hypotheses in the light of evidence. The computational model ECHO shows how explanatory coherence can be efficiently computed. We show the applicability of explanatory coherence to mental health assessment by modelling a case of psychiatric interviewing and a case of psychotherapeutic evaluation. We argue that this approach is more plausible than Bayesian inference and hermeneutic interpretation. © 2018 John Wiley & Sons, Ltd.

Comparing hospital costs: what is gained by accounting for more than a case-mix index?

PubMed

Hvenegaard, Anne; Street, Andrew; Sørensen, Torben Højmark; Gyrd-Hansen, Dorte

2009-08-01

We explore what effect controlling for various patient characteristics beyond a case-mix index (DRG) has on inferences drawn about the relative cost performance of hospital departments. We estimate fixed effect cost models in which 3754 patients are clustered within six Danish vascular departments. We compare a basic model including a DRG index only with models also including age and gender, health related characteristics, such as smoking status, diabetes, and American Society of Anesthesiogists score (ASA-score), and socioeconomic characteristics such as income, employment and whether the patient lives alone. We find that the DRG index is a robust and important explanatory factor and adding other routinely collected characteristics such as age and gender and other health related or socioeconomic characteristics do not seem to alter the results significantly. The results are more sensitive to choice of functional form, i.e. in particular to whether costs are log transformed. Our results suggest that the routinely collected characteristics such as DRG index, age and gender are sufficient when drawing inferences about relative cost performance. Adding health related or socioeconomic patient characteristics only slightly improves our model in terms of explanatory power but not when drawing inferences about relative performance. The results are, however, sensitive to whether costs are log transformed.

Interpreting the concordance statistic of a logistic regression model: relation to the variance and odds ratio of a continuous explanatory variable.

PubMed

Austin, Peter C; Steyerberg, Ewout W

2012-06-20

When outcomes are binary, the c-statistic (equivalent to the area under the Receiver Operating Characteristic curve) is a standard measure of the predictive accuracy of a logistic regression model. An analytical expression was derived under the assumption that a continuous explanatory variable follows a normal distribution in those with and without the condition. We then conducted an extensive set of Monte Carlo simulations to examine whether the expressions derived under the assumption of binormality allowed for accurate prediction of the empirical c-statistic when the explanatory variable followed a normal distribution in the combined sample of those with and without the condition. We also examine the accuracy of the predicted c-statistic when the explanatory variable followed a gamma, log-normal or uniform distribution in combined sample of those with and without the condition. Under the assumption of binormality with equality of variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the product of the standard deviation of the normal components (reflecting more heterogeneity) and the log-odds ratio (reflecting larger effects). Under the assumption of binormality with unequal variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the standardized difference of the explanatory variable in those with and without the condition. In our Monte Carlo simulations, we found that these expressions allowed for reasonably accurate prediction of the empirical c-statistic when the distribution of the explanatory variable was normal, gamma, log-normal, and uniform in the entire sample of those with and without the condition. The discriminative ability of a continuous explanatory variable cannot be judged by its odds ratio alone, but always needs to be considered in relation to the heterogeneity of the population.

Development of a neural-based forecasting tool to classify recreational water quality using fecal indicator organisms.

PubMed

Motamarri, Srinivas; Boccelli, Dominic L

2012-09-15

Users of recreational waters may be exposed to elevated pathogen levels through various point/non-point sources. Typical daily notifications rely on microbial analysis of indicator organisms (e.g., Escherichia coli) that require 18, or more, hours to provide an adequate response. Modeling approaches, such as multivariate linear regression (MLR) and artificial neural networks (ANN), have been utilized to provide quick predictions of microbial concentrations for classification purposes, but generally suffer from high false negative rates. This study introduces the use of learning vector quantization (LVQ)--a direct classification approach--for comparison with MLR and ANN approaches and integrates input selection for model development with respect to primary and secondary water quality standards within the Charles River Basin (Massachusetts, USA) using meteorologic, hydrologic, and microbial explanatory variables. Integrating input selection into model development showed that discharge variables were the most important explanatory variables while antecedent rainfall and time since previous events were also important. With respect to classification, all three models adequately represented the non-violated samples (>90%). The MLR approach had the highest false negative rates associated with classifying violated samples (41-62% vs 13-43% (ANN) and <16% (LVQ)) when using five or more explanatory variables. The ANN performance was more similar to LVQ when a larger number of explanatory variables were utilized, but the ANN performance degraded toward MLR performance as explanatory variables were removed. Overall, the use of LVQ as a direct classifier provided the best overall classification ability with respect to violated/non-violated samples for both standards. Copyright © 2012 Elsevier Ltd. All rights reserved.

The use of process models to inform and improve statistical models of nitrate occurrence, Great Miami River Basin, southwestern Ohio

USGS Publications Warehouse

Walter, Donald A.; Starn, J. Jeffrey

2013-01-01

Statistical models of nitrate occurrence in the glacial aquifer system of the northern United States, developed by the U.S. Geological Survey, use observed relations between nitrate concentrations and sets of explanatory variables—representing well-construction, environmental, and source characteristics— to predict the probability that nitrate, as nitrogen, will exceed a threshold concentration. However, the models do not explicitly account for the processes that control the transport of nitrogen from surface sources to a pumped well and use area-weighted mean spatial variables computed from within a circular buffer around the well as a simplified source-area conceptualization. The use of models that explicitly represent physical-transport processes can inform and, potentially, improve these statistical models. Specifically, groundwater-flow models simulate advective transport—predominant in many surficial aquifers— and can contribute to the refinement of the statistical models by (1) providing for improved, physically based representations of a source area to a well, and (2) allowing for more detailed estimates of environmental variables. A source area to a well, known as a contributing recharge area, represents the area at the water table that contributes recharge to a pumped well; a well pumped at a volumetric rate equal to the amount of recharge through a circular buffer will result in a contributing recharge area that is the same size as the buffer but has a shape that is a function of the hydrologic setting. These volume-equivalent contributing recharge areas will approximate circular buffers in areas of relatively flat hydraulic gradients, such as near groundwater divides, but in areas with steep hydraulic gradients will be elongated in the upgradient direction and agree less with the corresponding circular buffers. The degree to which process-model-estimated contributing recharge areas, which simulate advective transport and therefore account for local hydrologic settings, would inform and improve the development of statistical models can be implicitly estimated by evaluating the differences between explanatory variables estimated from the contributing recharge areas and the circular buffers used to develop existing statistical models. The larger the difference in estimated variables, the more likely that statistical models would be changed, and presumably improved, if explanatory variables estimated from contributing recharge areas were used in model development. Comparing model predictions from the two sets of estimated variables would further quantify—albeit implicitly—how an improved, physically based estimate of explanatory variables would be reflected in model predictions. Differences between the two sets of estimated explanatory variables and resultant model predictions vary spatially; greater differences are associated with areas of steep hydraulic gradients. A direct comparison, however, would require the development of a separate set of statistical models using explanatory variables from contributing recharge areas. Area-weighted means of three environmental variables—silt content, alfisol content, and depth to water from the U.S. Department of Agriculture State Soil Geographic (STATSGO) data—and one nitrogen-source variable (fertilizer-application rate from county data mapped to Enhanced National Land Cover Data 1992 (NLCDe 92) agricultural land use) can vary substantially between circular buffers and volume-equivalent contributing recharge areas and among contributing recharge areas for different sets of well variables. The differences in estimated explanatory variables are a function of the same factors affecting the contributing recharge areas as well as the spatial resolution and local distribution of the underlying spatial data. As a result, differences in estimated variables between circular buffers and contributing recharge areas are complex and site specific as evidenced by differences in estimated variables for circular buffers and contributing recharge areas of existing public-supply and network wells in the Great Miami River Basin. Large differences in areaweighted mean environmental variables are observed at the basin scale, determined by using the network of uniformly spaced hypothetical wells; the differences have a spatial pattern that generally is similar to spatial patterns in the underlying STATSGO data. Generally, the largest differences were observed for area-weighted nitrogen-application rate from county and national land-use data; the basin-scale differences ranged from -1,600 (indicating a larger value from within the volume-equivalent contributing recharge area) to 1,900 kilograms per year (kg/yr); the range in the underlying spatial data was from 0 to 2,200 kg/yr. Silt content, alfisol content, and nitrogen-application rate are defined by the underlying spatial data and are external to the groundwater system; however, depth to water is an environmental variable that can be estimated in more detail and, presumably, in a more physically based manner using a groundwater-flow model than using the spatial data. Model-calculated depths to water within circular buffers in the Great Miami River Basin differed substantially from values derived from the spatial data and had a much larger range. Differences in estimates of area-weighted spatial variables result in corresponding differences in predictions of nitrate occurrence in the aquifer. In addition to the factors affecting contributing recharge areas and estimated explanatory variables, differences in predictions also are a function of the specific set of explanatory variables used and the fitted slope coefficients in a given model. For models that predicted the probability of exceeding 1 and 4 milligrams per liter as nitrogen (mg/L as N), predicted probabilities using variables estimated from circular buffers and contributing recharge areas generally were correlated but differed significantly at the local and basin scale. The scale and distribution of prediction differences can be explained by the underlying differences in the estimated variables and the relative weight of the variables in the statistical models. Differences in predictions of exceeding 1 mg/L as N, which only includes environmental variables, generally correlated with the underlying differences in STATSGO data, whereas differences in exceeding 4 mg/L as N were more spatially extensive because that model included environmental and nitrogen-source variables. Using depths to water from within circular buffers derived from the spatial data and depths to water within the circular buffers calculated from the groundwater-flow model, restricted to the same range, resulted in large differences in predicted probabilities. The differences in estimated explanatory variables between contributing recharge areas and circular buffers indicate incorporation of physically based contributing recharge area likely would result in a different set of explanatory variables and an improved set of statistical models. The use of a groundwater-flow model to improve representations of source areas or to provide more-detailed estimates of specific explanatory variables includes a number of limitations and technical considerations. An assumption in these analyses is that (1) there is a state of mass balance between recharge and pumping, and (2) transport to a pumped well is under a steady state flow field. Comparison of volumeequivalent contributing recharge areas under steady-state and transient transport conditions at a location in the southeastern part of the basin shows the steady-state contributing recharge area is a reasonable approximation of the transient contributing recharge area after between 10 and 20 years of pumping. The first assumption is a more important consideration for this analysis. A gradient effect refers to a condition where simulated pumping from a well is less than recharge through the corresponding contributing recharge area. This generally takes place in areas with steep hydraulic gradients, such as near discharge locations, and can be mitigated using a finer model discretization. A boundary effect refers to a condition where recharge through the contributing recharge area is less than pumping. This indicates other sources of water to the simulated well and could reflect a real hydrologic process. In the Great Miami River Basin, large gradient and boundary effects—defined as the balance between pumping and recharge being less than half—occurred in 5 and 14 percent of the basin, respectively. The agreement between circular buffers and volume-equivalent contributing recharge areas, differences in estimated variables, and the effect on statisticalmodel predictions between the population of wells with a balance between pumping and recharge within 10 percent and the population of all wells were similar. This indicated process-model limitations did not affect the overall findings in the Great Miami River Basin; however, this would be model specific, and prudent use of a process model needs to entail a limitations analysis and, if necessary, alterations to the model.

Explanatory Power of Multi-scale Physical Descriptors in Modeling Benthic Indices Across Nested Ecoregions of the Pacific Northwest

NASA Astrophysics Data System (ADS)

Holburn, E. R.; Bledsoe, B. P.; Poff, N. L.; Cuhaciyan, C. O.

2005-05-01

Using over 300 R/EMAP sites in OR and WA, we examine the relative explanatory power of watershed, valley, and reach scale descriptors in modeling variation in benthic macroinvertebrate indices. Innovative metrics describing flow regime, geomorphic processes, and hydrologic-distance weighted watershed and valley characteristics are used in multiple regression and regression tree modeling to predict EPT richness, % EPT, EPT/C, and % Plecoptera. A nested design using seven ecoregions is employed to evaluate the influence of geographic scale and environmental heterogeneity on the explanatory power of individual and combined scales. Regression tree models are constructed to explain variability while identifying threshold responses and interactions. Cross-validated models demonstrate differences in the explanatory power associated with single-scale and multi-scale models as environmental heterogeneity is varied. Models explaining the greatest variability in biological indices result from multi-scale combinations of physical descriptors. Results also indicate that substantial variation in benthic macroinvertebrate response can be explained with process-based watershed and valley scale metrics derived exclusively from common geospatial data. This study outlines a general framework for identifying key processes driving macroinvertebrate assemblages across a range of scales and establishing the geographic extent at which various levels of physical description best explain biological variability. Such information can guide process-based stratification to avoid spurious comparison of dissimilar stream types in bioassessments and ensure that key environmental gradients are adequately represented in sampling designs.

Modeling ozone bioindicator injury with microscale and landscape-scale explanatory variables: A logistic regression approach

Treesearch

John W. Coulston

2011-01-01

Tropospheric ozone occurs at phytotoxic levels in the United States (Lefohn and Pinkerton 1988). Several plant species, including commercially important timber species, are sensitive to elevated ozone levels. Exposure to elevated ozone can cause growth reduction and foliar injury and make trees more susceptible to secondary stressors such as insects and pathogens (...

Explanatory model for sound amplification in a stethoscope

NASA Astrophysics Data System (ADS)

Eshach, H.; Volfson, A.

2015-01-01

In the present paper we suggest an original physical explanatory model that explains the mechanism of the sound amplification process in a stethoscope. We discuss the amplification of a single pulse, a continuous wave of certain frequency, and finally we address the resonant frequencies. It is our belief that this model may provide students with opportunities to not only better understand the amplification mechanism of a stethoscope, but also to strengthen their understanding of sound, pressure, waves, resonance modes, etc.

12 CFR Appendix A to Subpart A of... - Method to Derive Pricing Multipliers and Uniform Amount

Code of Federal Regulations, 2012 CFR

2012-01-01

... explanatory variables (regressors) in the model are six financial ratios and a weighted average of the “C,” “A,” “M,” “E” and “L” component ratings. The six financial ratios included in the model are: • Tier 1... downgraded to 3 or worse within 3 to 12 months from time T. The risk measures are financial ratios as defined...

12 CFR Appendix A to Subpart A of... - Method to Derive Pricing Multipliers and Uniform Amount

Code of Federal Regulations, 2014 CFR

2014-01-01

... explanatory variables (regressors) in the model are six financial ratios and a weighted average of the “C,” “A,” “M,” “E” and “L” component ratings. The six financial ratios included in the model are: • Tier 1... downgraded to 3 or worse within 3 to 12 months from time T. The risk measures are financial ratios as defined...

12 CFR Appendix A to Subpart A of... - Method to Derive Pricing Multipliers and Uniform Amount

Code of Federal Regulations, 2013 CFR

2013-01-01

... explanatory variables (regressors) in the model are six financial ratios and a weighted average of the “C,” “A,” “M,” “E” and “L” component ratings. The six financial ratios included in the model are: • Tier 1... downgraded to 3 or worse within 3 to 12 months from time T. The risk measures are financial ratios as defined...

Model for the separate collection of packaging waste in Portuguese low-performing recycling regions.

PubMed

Oliveira, V; Sousa, V; Vaz, J M; Dias-Ferreira, C

2018-06-15

Separate collection of packaging waste (glass; plastic/metals; paper/cardboard), is currently a widespread practice throughout Europe. It enables the recovery of good quality recyclable materials. However, separate collection performance are quite heterogeneous, with some countries reaching higher levels than others. In the present work, separate collection of packaging waste has been evaluated in a low-performance recycling region in Portugal in order to investigate which factors are most affecting the performance in bring-bank collection system. The variability of separate collection yields (kg per inhabitant per year) among 42 municipalities was scrutinized for the year 2015 against possible explanatory factors. A total of 14 possible explanatory factors were analysed, falling into two groups: socio-economic/demographic and waste collection service related. Regression models were built in an attempt to evaluate the individual effect of each factor on separate collection yields and predict changes on the collection yields by acting on those factors. The best model obtained is capable to explain 73% of the variation found in the separate collection yields. The model includes the following statistically significant indicators affecting the success of separate collection yields: i) inhabitants per bring-bank; ii) relative accessibility to bring-banks; iii) degree of urbanization; iv) number of school years attended; and v) area. The model presented in this work was developed specifically for the bring-bank system, has an explanatory power and quantifies the impact of each factor on separate collection yields. It can therefore be used as a support tool by local and regional waste management authorities in the definition of future strategies to increase collection of recyclables of good quality and to achieve national and regional targets. Copyright © 2017 Elsevier Ltd. All rights reserved.

An updated geospatial liquefaction model for global application

USGS Publications Warehouse

Zhu, Jing; Baise, Laurie G.; Thompson, Eric M.

2017-01-01

We present an updated geospatial approach to estimation of earthquake-induced liquefaction from globally available geospatial proxies. Our previous iteration of the geospatial liquefaction model was based on mapped liquefaction surface effects from four earthquakes in Christchurch, New Zealand, and Kobe, Japan, paired with geospatial explanatory variables including slope-derived VS30, compound topographic index, and magnitude-adjusted peak ground acceleration from ShakeMap. The updated geospatial liquefaction model presented herein improves the performance and the generality of the model. The updates include (1) expanding the liquefaction database to 27 earthquake events across 6 countries, (2) addressing the sampling of nonliquefaction for incomplete liquefaction inventories, (3) testing interaction effects between explanatory variables, and (4) overall improving model performance. While we test 14 geospatial proxies for soil density and soil saturation, the most promising geospatial parameters are slope-derived VS30, modeled water table depth, distance to coast, distance to river, distance to closest water body, and precipitation. We found that peak ground velocity (PGV) performs better than peak ground acceleration (PGA) as the shaking intensity parameter. We present two models which offer improved performance over prior models. We evaluate model performance using the area under the curve under the Receiver Operating Characteristic (ROC) curve (AUC) and the Brier score. The best-performing model in a coastal setting uses distance to coast but is problematic for regions away from the coast. The second best model, using PGV, VS30, water table depth, distance to closest water body, and precipitation, performs better in noncoastal regions and thus is the model we recommend for global implementation.

A new standard model for milk yield in dairy cows based on udder physiology at the milking-session level.

PubMed

Gasqui, Patrick; Trommenschlager, Jean-Marie

2017-08-21

Milk production in dairy cow udders is a complex and dynamic physiological process that has resisted explanatory modelling thus far. The current standard model, Wood's model, is empirical in nature, represents yield in daily terms, and was published in 1967. Here, we have developed a dynamic and integrated explanatory model that describes milk yield at the scale of the milking session. Our approach allowed us to formally represent and mathematically relate biological features of known relevance while accounting for stochasticity and conditional elements in the form of explicit hypotheses, which could then be tested and validated using real-life data. Using an explanatory mathematical and biological model to explore a physiological process and pinpoint potential problems (i.e., "problem finding"), it is possible to filter out unimportant variables that can be ignored, retaining only those essential to generating the most realistic model possible. Such modelling efforts are multidisciplinary by necessity. It is also helpful downstream because model results can be compared with observed data, via parameter estimation using maximum likelihood and statistical testing using model residuals. The process in its entirety yields a coherent, robust, and thus repeatable, model.

Spatial analysis of participation in the Waterloo Residential Energy Efficiency Project

NASA Astrophysics Data System (ADS)

Song, Ge Bella

Researchers are in broad agreement that energy-conserving actions produce economic as well as energy savings. Household energy rating systems (HERS) have been established in many countries to inform households of their house's current energy performance and to help reduce their energy consumption and greenhouse gas emissions. In Canada, the national EnerGuide for Houses (EGH) program is delivered by many local delivery agents, including non-profit green community organizations. Waterloo Region Green Solutions is the local non-profit that offers the EGH residential energy evaluation service to local households. The purpose of this thesis is to explore the determinants of household's participation in the residential energy efficiency program (REEP) in Waterloo Region, to explain the relationship between the explanatory variables and REEP participation, and to propose ways to improve this kind of program. A spatial (trend) analysis was conducted within a geographic information system (GIS) to determine the spatial patterns of the REEP participation in Waterloo Region from 1999 to 2006. The impact of sources of information on participation and relationships between participation rates and explanatory variables were identified. GIS proved successful in presenting a visual interpretation of spatial patterns of the REEP participation. In general, the participating households tend to be clustered in urban areas and scattered in rural areas. Different sources of information played significant roles in reaching participants in different years. Moreover, there was a relationship between each explanatory variable and the REEP participation rates. Statistical analysis was applied to obtain a quantitative assessment of relationships between hypothesized explanatory variables and participation in the REEP. The Poisson regression model was used to determine the relationship between hypothesized explanatory variables and REEP participation at the CDA level. The results show that all of the independent variables have a statistically significant positive relationship with REEP participation. These variables include level of education, average household income, employment rate, home ownership, population aged 65 and over, age of home, and number of eligible dwellings. The logistic regression model was used to assess the ability of the hypothesized explanatory variables to predict whether or not households would participate in a second follow-up evaluation after completing upgrades to their home. The results show all the explanatory variables have significant relationships with the dependent variable. The increased rating score, average household income, aged population, and age of home are positively related to the dependent variable. While the dwelling size and education has negative relationships with the dependent variable. In general, the contribution of this work provides a practical understanding of how the energy efficiency program operates, and insight into the type of variables that may be successful in bringing about changes in performance in the energy efficiency project in Waterloo Region. Secondly, with the completion of this research, future residential energy efficiency programs can use the information from this research and emulate or expand upon the efforts and lessons learned from the Residential Energy Efficiency Project in Waterloo Region case study. Thirdly, this research also contributes to practical experience on how to integrate different datasets using GIS.

The role of patients' explanatory models and daily-lived experience in hypertension self-management.

PubMed

Bokhour, Barbara G; Cohn, Ellen S; Cortés, Dharma E; Solomon, Jeffrey L; Fix, Gemmae M; Elwy, A Rani; Mueller, Nora; Katz, Lois A; Haidet, Paul; Green, Alexander R; Borzecki, Ann M; Kressin, Nancy R

2012-12-01

Uncontrolled hypertension remains a significant problem for many patients. Few interventions to improve patients' hypertension self-management have had lasting effects. Previous work has focused largely on patients' beliefs as predictors of behavior, but little is understood about beliefs as they are embedded in patients' social contexts. This study aims to explore how patients' "explanatory models" of hypertension (understandings of the causes, mechanisms or pathophysiology, course of illness, symptoms and effects of treatment) and social context relate to their reported daily hypertension self-management behaviors. Semi-structured qualitative interviews with a diverse group of patients at two large urban Veterans Administration Medical centers. PARTICIPANTS (OR PATIENTS OR SUBJECTS): African-American, white and Latino Veterans Affairs (VA) primary care patients with uncontrolled blood pressure. We conducted thematic analysis using tools of grounded theory to identify key themes surrounding patients' explanatory models, social context and hypertension management behaviors. Patients' perceptions of the cause and course of hypertension, experiences of hypertension symptoms, and beliefs about the effectiveness of treatment were related to different hypertension self-management behaviors. Moreover, patients' daily-lived experiences, such as an isolated lifestyle, serious competing health problems, a lack of habits and routines, barriers to exercise and prioritizing lifestyle choices, also interfered with optimal hypertension self-management. Designing interventions to improve patients' hypertension self-management requires consideration of patients' explanatory models and their daily-lived experience. We propose a new conceptual model - the dynamic model of hypertension self-management behavior - which incorporates these key elements of patients' experiences.

Response of benthic algae to environmental gradients in an agriculturally dominated landscape

USGS Publications Warehouse

Munn, M.D.; Black, R.W.; Gruber, S.J.

2002-01-01

Benthic algal communities were assessed in an agriculturally dominated landscape in the Central Columbia Plateau, Washington, to determine which environmental variables best explained species distributions, and whether algae species optima models were useful in predicting specific water-quality parameters. Land uses in the study area included forest, range, urban, and agriculture. Most of the streams in this region can be characterized as open-channel systems influenced by intensive dryland (nonirrigated) and irrigated agriculture. Algal communities in forested streams were dominated by blue-green algae, with communities in urban and range streams dominated by diatoms. The predominance of either blue-greens or diatoms in agricultural streams varied greatly depending on the specific site. Canonical correspondence analysis (CCA) indicated a strong gradient effect of several key environmental variables on benthic algal community composition. Conductivity and % agriculture were the dominant explanatory variables when all sites (n = 24) were included in the CCA; water velocity replaced conductivity when the CCA included only agricultural and urban sites. Other significant explanatory variables included dissolved inorganic nitrogen (DIN), orthophosphate (OP), discharge, and precipitation. Regression and calibration models accurately predicted conductivity based on benthic algal communities, with OP having slightly lower predictability. The model for DIN was poor, and therefore may be less useful in this system. Thirty-four algal taxa were identified as potential indicators of conductivity and nutrient conditions, with most indicators being diatoms except for the blue-greens Anabaenasp. and Lyngbya sp.

Modelling sociocognitive aspects of students' learning

NASA Astrophysics Data System (ADS)

Koponen, I. T.; Kokkonen, T.; Nousiainen, M.

2017-03-01

We present a computational model of sociocognitive aspects of learning. The model takes into account a student's individual cognition and sociodynamics of learning. We describe cognitive aspects of learning as foraging for explanations in the epistemic landscape, the structure (set by instructional design) of which guides the cognitive development through success or failure in foraging. We describe sociodynamic aspects as an agent-based model, where agents (learners) compare and adjust their conceptions of their own proficiency (self-proficiency) and that of their peers (peer-proficiency) in using explanatory schemes of different levels. We apply the model here in a case involving a three-tiered system of explanatory schemes, which can serve as a generic description of some well-known cases studied in empirical research on learning. The cognitive dynamics lead to the formation of dynamically robust outcomes of learning, seen as a strong preference for a certain explanatory schemes. The effects of social learning, however, can account for half of one's success in adopting higher-level schemes and greater proficiency. The model also predicts a correlation of dynamically emergent interaction patterns between agents and the learning outcomes.

CAVEing the MMPI for an Optimism-Pessimism Scale: Seligman's Attributional Model and the Assessment of Explanatory Style.

ERIC Educational Resources Information Center

Colligan, Robert C.; And Others

1994-01-01

Developed bipolar Minnesota Multiphasic Personality Inventory (MMPI) Optimism-Pessimism (PSM) scale based on results on Content Analysis of Verbatim Explanation applied to MMPI. Reliability and validity indices show that PSM scale is highly accurate and consistent with Seligman's theory that pessimistic explanatory style predicts increased…

Modeling and mapping abundance of American Woodcock across the Midwestern and Northeastern United States

USGS Publications Warehouse

Thogmartin, W.E.; Sauer, J.R.; Knutson, M.G.

2007-01-01

We used an over-dispersed Poisson regression with fixed and random effects, fitted by Markov chain Monte Carlo methods, to model population spatial patterns of relative abundance of American woodcock (Scolopax minor) across its breeding range in the United States. We predicted North American woodcock Singing Ground Survey counts with a log-linear function of explanatory variables describing habitat, year effects, and observer effects. The model also included a conditional autoregressive term representing potential correlation between adjacent route counts. Categories of explanatory habitat variables in the model included land-cover composition, climate, terrain heterogeneity, and human influence. Woodcock counts were higher in landscapes with more forest, especially aspen (Populus tremuloides) and birch (Betula spp.) forest, and in locations with a high degree of interspersion among forest, shrubs, and grasslands. Woodcock counts were lower in landscapes with a high degree of human development. The most noteworthy practical application of this spatial modeling approach was the ability to map predicted relative abundance. Based on a map of predicted relative abundance derived from the posterior parameter estimates, we identified major concentrations of woodcock abundance in east-central Minnesota, USA, the intersection of Vermont, USA, New York, USA, and Ontario, Canada, the upper peninsula of Michigan, USA, and St. Lawrence County, New York. The functional relations we elucidated for the American woodcock provide a basis for the development of management programs and the model and map may serve to focus management and monitoring on areas and habitat features important to American woodcock.

A Unified Framework for Association Analysis with Multiple Related Phenotypes

PubMed Central

Stephens, Matthew

2013-01-01

We consider the problem of assessing associations between multiple related outcome variables, and a single explanatory variable of interest. This problem arises in many settings, including genetic association studies, where the explanatory variable is genotype at a genetic variant. We outline a framework for conducting this type of analysis, based on Bayesian model comparison and model averaging for multivariate regressions. This framework unifies several common approaches to this problem, and includes both standard univariate and standard multivariate association tests as special cases. The framework also unifies the problems of testing for associations and explaining associations – that is, identifying which outcome variables are associated with genotype. This provides an alternative to the usual, but conceptually unsatisfying, approach of resorting to univariate tests when explaining and interpreting significant multivariate findings. The method is computationally tractable genome-wide for modest numbers of phenotypes (e.g. 5–10), and can be applied to summary data, without access to raw genotype and phenotype data. We illustrate the methods on both simulated examples, and to a genome-wide association study of blood lipid traits where we identify 18 potential novel genetic associations that were not identified by univariate analyses of the same data. PMID:23861737

Agricultural disturbance response models for invertebrate and algal metrics from streams at two spatial scales within the U.S.

USGS Publications Warehouse

Waite, Ian R.

2014-01-01

As part of the USGS study of nutrient enrichment of streams in agricultural regions throughout the United States, about 30 sites within each of eight study areas were selected to capture a gradient of nutrient conditions. The objective was to develop watershed disturbance predictive models for macroinvertebrate and algal metrics at national and three regional landscape scales to obtain a better understanding of important explanatory variables. Explanatory variables in models were generated from landscape data, habitat, and chemistry. Instream nutrient concentration and variables assessing the amount of disturbance to the riparian zone (e.g., percent row crops or percent agriculture) were selected as most important explanatory variable in almost all boosted regression tree models regardless of landscape scale or assemblage. Frequently, TN and TP concentration and riparian agricultural land use variables showed a threshold type response at relatively low values to biotic metrics modeled. Some measure of habitat condition was also commonly selected in the final invertebrate models, though the variable(s) varied across regions. Results suggest national models tended to account for more general landscape/climate differences, while regional models incorporated both broad landscape scale and more specific local-scale variables.

Interpreting the concordance statistic of a logistic regression model: relation to the variance and odds ratio of a continuous explanatory variable

PubMed Central

2012-01-01

Background When outcomes are binary, the c-statistic (equivalent to the area under the Receiver Operating Characteristic curve) is a standard measure of the predictive accuracy of a logistic regression model. Methods An analytical expression was derived under the assumption that a continuous explanatory variable follows a normal distribution in those with and without the condition. We then conducted an extensive set of Monte Carlo simulations to examine whether the expressions derived under the assumption of binormality allowed for accurate prediction of the empirical c-statistic when the explanatory variable followed a normal distribution in the combined sample of those with and without the condition. We also examine the accuracy of the predicted c-statistic when the explanatory variable followed a gamma, log-normal or uniform distribution in combined sample of those with and without the condition. Results Under the assumption of binormality with equality of variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the product of the standard deviation of the normal components (reflecting more heterogeneity) and the log-odds ratio (reflecting larger effects). Under the assumption of binormality with unequal variances, the c-statistic follows a standard normal cumulative distribution function with dependence on the standardized difference of the explanatory variable in those with and without the condition. In our Monte Carlo simulations, we found that these expressions allowed for reasonably accurate prediction of the empirical c-statistic when the distribution of the explanatory variable was normal, gamma, log-normal, and uniform in the entire sample of those with and without the condition. Conclusions The discriminative ability of a continuous explanatory variable cannot be judged by its odds ratio alone, but always needs to be considered in relation to the heterogeneity of the population. PMID:22716998

An Explanatory Model of Poverty from the Perspective of Social Psychology and Human Rights.

PubMed

Pérez-Muñoz, Alfonso; Chacón, Fernando; Martínez Arias, Rosario

2015-12-09

Poverty is a social problem, entailing not only an economical perspective but above all a human and social issue. Poverty is promoted, justified and maintained by unique individuals and groups by means of our own attitudes, interests and behavior, as well as with our social structures and social relationships. From this interactive, psychosocial and sociostructural perspective, and also considering poverty as a denial of basic human rights (UNDP, 1998), we carried out a study with the primary objective to design and verify an Explanatory Model of Poverty. This research may helps to increase the validity of diagnostics and the effectiveness of interventions. Most of the hypotheses were accepted during the analysis and verification of the Model (p < .001), with data fitting the Model (CFI: 1 RMSEA: .025: LO90: 0 - HI90: .061. RMR: .008). These results, if replicated in new investigations, could have the following implications: (a) the need for a broad and comprehensive definition of poverty including its effects, processes and causes; (b) the need for everybody to accept the social responsibility in the prevention and solution to poverty; and (c) the need to conduct longitudinal interventions with scientific methodology and social participation.

Regression Analysis of Stage Variability for West-Central Florida Lakes

USGS Publications Warehouse

Sacks, Laura A.; Ellison, Donald L.; Swancar, Amy

2008-01-01

The variability in a lake's stage depends upon many factors, including surface-water flows, meteorological conditions, and hydrogeologic characteristics near the lake. An understanding of the factors controlling lake-stage variability for a population of lakes may be helpful to water managers who set regulatory levels for lakes. The goal of this study is to determine whether lake-stage variability can be predicted using multiple linear regression and readily available lake and basin characteristics defined for each lake. Regressions were evaluated for a recent 10-year period (1996-2005) and for a historical 10-year period (1954-63). Ground-water pumping is considered to have affected stage at many of the 98 lakes included in the recent period analysis, and not to have affected stage at the 20 lakes included in the historical period analysis. For the recent period, regression models had coefficients of determination (R2) values ranging from 0.60 to 0.74, and up to five explanatory variables. Standard errors ranged from 21 to 37 percent of the average stage variability. Net leakage was the most important explanatory variable in regressions describing the full range and low range in stage variability for the recent period. The most important explanatory variable in the model predicting the high range in stage variability was the height over median lake stage at which surface-water outflow would occur. Other explanatory variables in final regression models for the recent period included the range in annual rainfall for the period and several variables related to local and regional hydrogeology: (1) ground-water pumping within 1 mile of each lake, (2) the amount of ground-water inflow (by category), (3) the head gradient between the lake and the Upper Floridan aquifer, and (4) the thickness of the intermediate confining unit. Many of the variables in final regression models are related to hydrogeologic characteristics, underscoring the importance of ground-water exchange in controlling the stage of karst lakes in Florida. Regression equations were used to predict lake-stage variability for the recent period for 12 additional lakes, and the median difference between predicted and observed values ranged from 11 to 23 percent. Coefficients of determination for the historical period were considerably lower (maximum R2 of 0.28) than for the recent period. Reasons for these low R2 values are probably related to the small number of lakes (20) with stage data for an equivalent time period that were unaffected by ground-water pumping, the similarity of many of the lake types (large surface-water drainage lakes), and the greater uncertainty in defining historical basin characteristics. The lack of lake-stage data unaffected by ground-water pumping and the poor regression results obtained for that group of lakes limit the ability to predict natural lake-stage variability using this method in west-central Florida.

Human vs. Computer Diagnosis of Students' Natural Selection Knowledge: Testing the Efficacy of Text Analytic Software

ERIC Educational Resources Information Center

Nehm, Ross H.; Haertig, Hendrik

2012-01-01

Our study examines the efficacy of Computer Assisted Scoring (CAS) of open-response text relative to expert human scoring within the complex domain of evolutionary biology. Specifically, we explored whether CAS can diagnose the explanatory elements (or Key Concepts) that comprise undergraduate students' explanatory models of natural selection with…

Schoolyard Science. Grades 2-4.

ERIC Educational Resources Information Center

Perdue, Peggy K.

This book includes 25 science activities in the fields of environmental science, soil science, life science, and physical science. The activities are designed to be used in outdoor settings. Each activity is composed of two parts--an explanatory section for the teacher and a student lab sheet. The teacher explanatory section begins with a brief…

unmarked: An R package for fitting hierarchical models of wildlife occurrence and abundance

USGS Publications Warehouse

Fiske, Ian J.; Chandler, Richard B.

2011-01-01

Ecological research uses data collection techniques that are prone to substantial and unique types of measurement error to address scientific questions about species abundance and distribution. These data collection schemes include a number of survey methods in which unmarked individuals are counted, or determined to be present, at spatially- referenced sites. Examples include site occupancy sampling, repeated counts, distance sampling, removal sampling, and double observer sampling. To appropriately analyze these data, hierarchical models have been developed to separately model explanatory variables of both a latent abundance or occurrence process and a conditional detection process. Because these models have a straightforward interpretation paralleling mechanisms under which the data arose, they have recently gained immense popularity. The common hierarchical structure of these models is well-suited for a unified modeling interface. The R package unmarked provides such a unified modeling framework, including tools for data exploration, model fitting, model criticism, post-hoc analysis, and model comparison.

Learned social hopelessness: the role of explanatory style in predicting social support during adolescence.

PubMed

Ciarrochi, Joseph; Heaven, Patrick C L

2008-12-01

Almost no research has examined the impact of explanatory style on social adjustment. We hypothesised that adolescents with a pessimistic style would be less likely to develop and maintain social support networks. Seven hundred and nineteen students (351 males and 366 females; 2 unknown; M(AGE) = 12.28, SD = .49) completed an anonymous survey in Grades 7 through 10. Explanatory style was assessed in Grades 7 and 9, sadness was assessed in Grades 7 through 10, and quantity and quality of social support was assessed in Grades 8, 9, and 10. Structural equation modelling was used to conduct cross-lagged panel analyses of the four waves of data. Pessimistic explanatory style predicted lower levels of social support, and lower social support from the family predicted higher levels of pessimistic explanatory style. Additional analyses suggested that the effects could not be explained by sadness or by assuming that pessimistic adolescents where less liked by their peers. Pessimistic adolescents feel unable to influence their social worlds in positive ways and consequently may not take actions to develop and maintain social support networks.

Using Computers Intelligently in Tertiary Education. A Collection of Papers Presented to the Australian Society for Computers in Learning (Sydney, New South Wales, Australia, November 29-December 3, 1987).

ERIC Educational Resources Information Center

Barrett, John, Ed.; Hedberg, John, Ed.

The 63 papers in this collection include two keynote addresses: "Patient Simulation Using Interactive Video: An Application" (Joseph V. Henderson), and "Intelligent Tutoring Systems: Practice Opportunities and Explanatory Models" (Alan Lesgold). The remaining papers are grouped under five topics: (1) Artificial Intelligence,…

Identifying Indicators of State Change and Forecasting Future Vulnerability in Alaskan Boreal Ecosystems

DTIC Science & Technology

2016-08-01

catastrophic effects on facilities, infrastructure, and military testing and training. Permafrost temperature , thickness, and geographic continuity...and fire severity (~0 to ~100% SOL consumption ), they provide an excellent suite of sites to test and quantify the effects of fire severity on plant...59 Table 6.1. Variables included in explanatory matrix for black spruce dominance ............68 Table 6.2. Mixed effect model

Locating the Social Origins of Mental Illness: The Explanatory Models of Mental Illness Among Clergy from Different Ethnic and Faith Backgrounds.

PubMed

Leavey, Gerard; Loewenthal, Kate; King, Michael

2016-10-01

Clergy have historically provided 'healing' through various spiritual and medical modalities and even in modern, developed welfare economies they may still be an important help-seeking resource. Partnerships between religion and psychiatry are regularly advocated, but there is scant research on clergy explanatory models of illness. This paper aimed to explore their relationship with psychiatry and to examine how clergy in various faith groups conceptualised mental health problems. In this qualitative study using in-depth interviews, these issues were explored with 32 practising clergy in the UK from a range of different Christian, Muslim and Jewish faith organisations and ethnic backgrounds. This paper presents findings related to clergy explanatory models of mental illness and, in particular, how the social factors involved in causation are tinged with spiritual influences and implications, and how the meanings of mental distress assume a social and moral significance in distinctive localised matters.

Attitudinal and behavioral characteristics predict high risk sexual activity in rural Tanzanian youth.

PubMed

Aichele, Stephen R; Borgerhoff Mulder, Monique; James, Susan; Grimm, Kevin

2014-01-01

The incidence of HIV infection in rural African youth remains high despite widespread knowledge of the disease within the region and increasing funds allocated to programs aimed at its prevention and treatment. This suggests that program efficacy requires a more nuanced understanding of the profiles of the most at-risk individuals. To evaluate the explanatory power of novel psychographic variables in relation to high-risk sexual behaviors, we conducted a survey to assess the effects of psychographic factors, both behavioral and attitudinal, controlling for standard predictors in 546 youth (12-26 years of age) across 8 villages in northern Tanzania. Indicators of high-risk sexual behavior included HIV testing, sexual history (i.e., virgin/non-virgin), age of first sexual activity, condom use, and number of lifetime sexual partners. Predictors in the statistical models included standard demographic variables, patterns of media consumption, HIV awareness, and six new psychographic features identified via factor analyses: personal vanity, family-building values, ambition for higher education, town recreation, perceived parental strictness, and spending preferences. In a series of hierarchical regression analyses, we find that models including psychographic factors contribute significant additional explanatory information when compared to models including only demographic and other conventional predictors. We propose that the psychographic approach used here, in so far as it identifies individual characteristics, aspirations, aspects of personal life style and spending preferences, can be used to target appropriate communities of youth within villages for leading and receiving outreach, and to build communities of like-minded youth who support new patterns of sexual behavior.

Science Is an Action Word! Grades 1-3.

ERIC Educational Resources Information Center

Perdue, Peggy K.

This book includes 20 science activities in the fields of scientific method, earth science, life science, and physical science. Each activity is composed of two parts--an explanatory section for the teacher and a student lab sheet. The explanatory section begins with a brief introduction designed to give an overview of the activity's main concept.…

Using Indirect Turbulence Measurements for Real-Time Parameter Estimation in Turbulent Air

NASA Technical Reports Server (NTRS)

Martos, Borja; Morelli, Eugene A.

2012-01-01

The use of indirect turbulence measurements for real-time estimation of parameters in a linear longitudinal dynamics model in atmospheric turbulence was studied. It is shown that measuring the atmospheric turbulence makes it possible to treat the turbulence as a measured explanatory variable in the parameter estimation problem. Commercial off-the-shelf sensors were researched and evaluated, then compared to air data booms. Sources of colored noise in the explanatory variables resulting from typical turbulence measurement techniques were identified and studied. A major source of colored noise in the explanatory variables was identified as frequency dependent upwash and time delay. The resulting upwash and time delay corrections were analyzed and compared to previous time shift dynamic modeling research. Simulation data as well as flight test data in atmospheric turbulence were used to verify the time delay behavior. Recommendations are given for follow on flight research and instrumentation.

A Study of Effects of MultiCollinearity in the Multivariable Analysis

PubMed Central

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; (Peter) He, Qinghua; Lillard, James W.

2015-01-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables. PMID:25664257

A Study of Effects of MultiCollinearity in the Multivariable Analysis.

PubMed

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; Peter He, Qinghua; Lillard, James W

2014-10-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables.

Performance of comorbidity, risk adjustment, and functional status measures in expenditure prediction for patients with diabetes.

PubMed

Maciejewski, Matthew L; Liu, Chuan-Fen; Fihn, Stephan D

2009-01-01

To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes. This study included a retrospective cohort of 3,092 diabetic veterans participating in a multisite trial. Two comorbidity measures, four risk adjusters, a functional status measure, a diabetes complication count, and baseline expenditures were constructed from administrative and survey data. Outpatient, inpatient, and total expenditure models were estimated using ordinary least squares regression. Adjusted R(2) statistics and predictive ratios were compared across measures to assess overall explanatory power and explanatory power of low- and high-cost subgroups. Administrative data-based risk adjusters performed better than the comorbidity, functional status, and diabetes-specific measures in all expenditure models. The diagnostic cost groups (DCGs) measure had the greatest predictive power overall and for the low- and high-cost subgroups, while the diabetes-specific measure had the lowest predictive power. A model with DCGs and the diabetes-specific measure modestly improved predictive power. Existing generic measures can be useful for diabetes-specific research and policy applications, but more predictive diabetes-specific measures are needed.

Insight in psychosis: an independent predictor of outcome or an explanatory model of illness?

PubMed

Jacob, K S

2014-10-01

While the traditional view within psychiatry is that insight is independent of psychopathology and predicts the course and outcome of psychosis, recent data from India argues that insight is secondary to interaction between progression of illness on one hand and local culture and social environment on the other. The findings suggest that "insight" is an explanatory model (EM) and may reflect attempts at coping with the devastating effects of mental disorders. Most societies are pluralistic and offer multiple, divergent and contradictory explanations for illnesses. These belief systems interact with the trajectory of the person's illness to produce a unique personal understanding, often based on a set of complex and contradictory EMs. Like all EMs, insight provides meaning to explain and overcome challenges including disabling symptoms, persistent deficits, impaired social relations and difficult livelihood issues. The persistence of distress, impairment, disability and handicap, despite regular and optimal treatment, call for explanations, which go beyond the simplistic concept of disease. People tend to choose EMs, which are non-stigmatizing and which seem to help explain and rationalize their individual concerns. The frequent presence of multiple and often contradictory EMs, held simultaneously, suggest that they are pragmatic responses at coping. The results advocate a non-judgmental approach and broad based assessment of EMs of illness and their comparison with culturally appropriate beliefs, attributions and actions. The biomedical model of illness should be presented without dismissing patient beliefs or belittling local cultural explanations for illness. Clinical practice demands a negotiation of shared model of care and treatment plan between patient and physician perspectives. The diversity of patients, problems, beliefs and cultures mandates the need to educate, match, negotiate and integrate psychiatric and psychological frameworks and interventions. It calls for multifaceted and nuanced understanding of "insight" and explanatory models of illness. Copyright © 2014 Elsevier B.V. All rights reserved.

Direction dependence analysis: A framework to test the direction of effects in linear models with an implementation in SPSS.

PubMed

Wiedermann, Wolfgang; Li, Xintong

2018-04-16

In nonexperimental data, at least three possible explanations exist for the association of two variables x and y: (1) x is the cause of y, (2) y is the cause of x, or (3) an unmeasured confounder is present. Statistical tests that identify which of the three explanatory models fits best would be a useful adjunct to the use of theory alone. The present article introduces one such statistical method, direction dependence analysis (DDA), which assesses the relative plausibility of the three explanatory models on the basis of higher-moment information about the variables (i.e., skewness and kurtosis). DDA involves the evaluation of three properties of the data: (1) the observed distributions of the variables, (2) the residual distributions of the competing models, and (3) the independence properties of the predictors and residuals of the competing models. When the observed variables are nonnormally distributed, we show that DDA components can be used to uniquely identify each explanatory model. Statistical inference methods for model selection are presented, and macros to implement DDA in SPSS are provided. An empirical example is given to illustrate the approach. Conceptual and empirical considerations are discussed for best-practice applications in psychological data, and sample size recommendations based on previous simulation studies are provided.

Global effects of local human population density and distance to markets on the condition of coral reef fisheries.

PubMed

Cinner, Joshua E; Graham, Nicholas A J; Huchery, Cindy; Macneil, M Aaron

2013-06-01

Coral reef fisheries support the livelihoods of millions of people but have been severely and negatively affected by anthropogenic activities. We conducted a systematic review of published data on the biomass of coral reef fishes to explore how the condition of reef fisheries is related to the density of local human populations, proximity of the reef to markets, and key environmental variables (including broad geomorphologic reef type, reef area, and net productivity). When only population density and environmental covariates were considered, high variability in fisheries conditions at low human population densities resulted in relatively weak explanatory models. The presence or absence of human settlements, habitat type, and distance to fish markets provided a much stronger explanatory model for the condition of reef fisheries. Fish biomass remained relatively low within 14 km of markets, then biomass increased exponentially as distance from reefs to markets increased. Our results suggest the need for an increased science and policy focus on markets as both a key driver of the condition of reef fisheries and a potential source of solutions. © 2012 Society for Conservation Biology.

[Functional somatic syndromes from the view of cultural anthropology].

PubMed

Nakagami, Ayako; Tsujiuchi, Takuya

2009-09-01

The functional somatic syndromes have acquired major socio-cultural and political dimensions. Socio-cultural factors clearly affect symptoms, suffering, and disability perception and reporting. And knowledge of explanatory models of bodily distress for patients from different cultural backgrounds is useful in the establishment of a stable doctor -patient relationship. FSS may be an operational category to bridge between medical explanatory model and patient's model. According to medical anthropology, sickness has two faces; illness and disease. "Disease" is the problem from the practitioner's perspective, and "illness" is the human experience of symptoms and suffering. In this paper, the anthropological research on chronic fatigue syndrome as "not real" illness experience was described.

Explanatory model of emotional-cognitive variables in school mathematics performance: a longitudinal study in primary school.

PubMed

Cerda, Gamal; Pérez, Carlos; Navarro, José I; Aguilar, Manuel; Casas, José A; Aragón, Estíbaliz

2015-01-01

This study tested a structural model of cognitive-emotional explanatory variables to explain performance in mathematics. The predictor variables assessed were related to students' level of development of early mathematical competencies (EMCs), specifically, relational and numerical competencies, predisposition toward mathematics, and the level of logical intelligence in a population of primary school Chilean students (n = 634). This longitudinal study also included the academic performance of the students during a period of 4 years as a variable. The sampled students were initially assessed by means of an Early Numeracy Test, and, subsequently, they were administered a Likert-type scale to measure their predisposition toward mathematics (EPMAT) and a basic test of logical intelligence. The results of these tests were used to analyse the interaction of all the aforementioned variables by means of a structural equations model. This combined interaction model was able to predict 64.3% of the variability of observed performance. Preschool students' performance in EMCs was a strong predictor for achievement in mathematics for students between 8 and 11 years of age. Therefore, this paper highlights the importance of EMCs and the modulating role of predisposition toward mathematics. Also, this paper discusses the educational role of these findings, as well as possible ways to improve negative predispositions toward mathematical tasks in the school domain.

The Perfect Storm: Preterm Birth, Neurodevelopmental Mechanisms, and Autism Causation.

PubMed

Erdei, Carmina; Dammann, Olaf

2014-01-01

A unifying model of autism causation remains elusive, and thus well-designed explanatory models are needed to develop appropriate therapeutic and preventive interventions. This essay argues that autism is not a static disorder, but rather an ongoing process. We discuss the link between preterm birth and autism and briefly review the evidence supporting the link between immune system characteristics and both prematurity and autism. We then propose a causation process model of autism etiology and pathogenesis, in which both neurodevelopment and ongoing/prolonged neuroinflammation are necessary pathogenetic component mechanisms. We suggest that an existing model of sufficient cause and component causes can be interpreted as a mechanistic view of etiology and pathogenesis and can serve as an explanatory model for autism causal pathways.

A Pessimistic Explanatory Style is Prognostic for Poor Lung Cancer Survival

PubMed Central

Novotny, Paul; Colligan, Robert C.; Szydlo, Daniel W.; Clark, Matthew M.; Rausch, Sarah; Wampfler, Jason; Sloan, Jeff A.; Yang, Ping

2010-01-01

Background Several studies have demonstrated the importance of personality constructs on health behaviors and health status. Having a pessimistic outlook has been related to negative health behaviors and higher mortality. However, the construct has not been well explored in cancer populations. Methods Survival time of 534 adults, who were diagnosed with lung cancer and had a pessimistic explanatory style, was examined. The patients had completed the Minnesota Multiphasic Personality Inventory (MMPI) approximately 18.2 years prior to receiving their lung cancer diagnosis. MMPI Optimism-Pessimism (PSM) scores were divided into high (60 or more) and low scores (less than 60), and log-rank tests and Kaplan-Meier curves were used to determine survival differences. Multivariate Cox models were used for assessing prognostic values of pessimism along with other known predictors for lung cancer survival outcome. Booting strapping of the survival models was used as a sensitivity analysis. Results At the time of lung cancer diagnosis, patients were on average 67 years old; 48% were female; 85% had non-small cell lung cancer (NSCLC); 15% had small cell lung cancer (SCLC); 30% were stage I; 4% were stage II; 31% were stage III/limited; and 35% were stage IV/extensive. Patients who exhibited a non-pessimistic explanatory style survived approximately six months longer than patients classified as having a pessimistic explanatory style. Conclusion Among lung cancer patients, those having a pessimistic explanatory style experienced less favorable survival outcome, which may be related to cancer treatment decisions. Further research in this area is warranted. PMID:20139778

The extension of total gain (TG) statistic in survival models: properties and applications.

PubMed

Choodari-Oskooei, Babak; Royston, Patrick; Parmar, Mahesh K B

2015-07-01

The results of multivariable regression models are usually summarized in the form of parameter estimates for the covariates, goodness-of-fit statistics, and the relevant p-values. These statistics do not inform us about whether covariate information will lead to any substantial improvement in prediction. Predictive ability measures can be used for this purpose since they provide important information about the practical significance of prognostic factors. R (2)-type indices are the most familiar forms of such measures in survival models, but they all have limitations and none is widely used. In this paper, we extend the total gain (TG) measure, proposed for a logistic regression model, to survival models and explore its properties using simulations and real data. TG is based on the binary regression quantile plot, otherwise known as the predictiveness curve. Standardised TG ranges from 0 (no explanatory power) to 1 ('perfect' explanatory power). The results of our simulations show that unlike many of the other R (2)-type predictive ability measures, TG is independent of random censoring. It increases as the effect of a covariate increases and can be applied to different types of survival models, including models with time-dependent covariate effects. We also apply TG to quantify the predictive ability of multivariable prognostic models developed in several disease areas. Overall, TG performs well in our simulation studies and can be recommended as a measure to quantify the predictive ability in survival models.

Using Explanatory Item Response Models to Evaluate Complex Scientific Tasks Designed for the Next Generation Science Standards

NASA Astrophysics Data System (ADS)

Chiu, Tina

This dissertation includes three studies that analyze a new set of assessment tasks developed by the Learning Progressions in Middle School Science (LPS) Project. These assessment tasks were designed to measure science content knowledge on the structure of matter domain and scientific argumentation, while following the goals from the Next Generation Science Standards (NGSS). The three studies focus on the evidence available for the success of this design and its implementation, generally labelled as "validity" evidence. I use explanatory item response models (EIRMs) as the overarching framework to investigate these assessment tasks. These models can be useful when gathering validity evidence for assessments as they can help explain student learning and group differences. In the first study, I explore the dimensionality of the LPS assessment by comparing the fit of unidimensional, between-item multidimensional, and Rasch testlet models to see which is most appropriate for this data. By applying multidimensional item response models, multiple relationships can be investigated, and in turn, allow for a more substantive look into the assessment tasks. The second study focuses on person predictors through latent regression and differential item functioning (DIF) models. Latent regression models show the influence of certain person characteristics on item responses, while DIF models test whether one group is differentially affected by specific assessment items, after conditioning on latent ability. Finally, the last study applies the linear logistic test model (LLTM) to investigate whether item features can help explain differences in item difficulties.

Extending the explanatory utility of the EPPM beyond fear-based persuasion.

PubMed

Lewis, Ioni; Watson, Barry; White, Katherine M

2013-01-01

In the 20 years since its inception, the Extended Parallel Process Model (EPPM) has attracted much empirical support. Currently, and unsurprisingly, given that is a model of fear-based persuasion, the EPPM's explanatory utility has been based only upon fear-based messages. However, an argument is put forth herein that draws upon existing evidence that the EPPM may be an efficacious framework for explaining the persuasive process and outcomes of emotion-based messages more broadly when such messages are addressing serious health topics. For the current study, four different types of emotional appeals were purposefully devised and included a fear-, an annoyance/agitation-, a pride-, and a humor-based message. All messages addressed the serious health issue of road safety, and in particular the risky behavior of speeding. Participants (n = 551) were exposed to only one of the four messages and subsequently provided responses within a survey. A series of 2 (threat: low, high) × 2 (efficacy: low, high) analysis of variance was conducted for each of the appeals based on the EPPM's message outcomes of acceptance and rejection. Support was found for the EPPM with a number of main effects of threat and efficacy emerging, reflecting that, irrespective of emotional appeal type, high levels of threat and efficacy enhanced message outcomes via maximizing acceptance and minimizing rejection. Theoretically, the findings provide support for the explanatory utility of the EPPM for emotion-based health messages more broadly. In an applied sense, the findings highlight the value of adopting the EPPM as a framework when devising and evaluating emotion-based health messages for serious health topics.

A case study of alternative site response explanatory variables in Parkfield, California

USGS Publications Warehouse

Thompson, E.M.; Baise, L.G.; Kayen, R.E.; Morgan, E.C.; Kaklamanos, J.

2011-01-01

The combination of densely-spaced strong-motion stations in Parkfield, California, and spectral analysis of surface waves (SASW) profiles provides an ideal dataset for assessing the accuracy of different site response explanatory variables. We judge accuracy in terms of spatial coverage and correlation with observations. The performance of the alternative models is period-dependent, but generally we observe that: (1) where a profile is available, the square-root-of-impedance method outperforms VS30 (average S-wave velocity to 30 m depth), and (2) where a profile is unavailable, the topographic-slope method outperforms surficial geology. The fundamental site frequency is a valuable site response explanatory variable, though less valuable than VS30. However, given the expense and difficulty of obtaining reliable estimates of VS30 and the relative ease with which the fundamental site frequency can be computed, the fundamental site frequency may prove to be a valuable site response explanatory variable for many applications. ?? 2011 ASCE.

Explanatory Style in Patients with Rheumatoid Arthritis: An Unrecognized Predictor of Mortality

PubMed Central

Crowson, Aaron D.; Colligan, Robert C.; Matteson, Eric L.; Davis, John M.; Crowson, Cynthia S.

2016-01-01

Objective To determine whether pessimistic explanatory style altered the risk for and mortality of rheumatoid arthritis (RA) patients. Methods The study included subjects from a population-based cohort with incident RA and non-RA comparison cohort who completed the Minnesota Multiphasic Personality Inventory (MMPI). Results Among 148 RA and 135 non-RA subjects, pessimism was associated with development of rheumatoid factor positive (RF+) RA. Pessimism was associated with an increased risk of mortality (hazard ratio [HR]:2.88 with similar magnitude to RF+ (HR:2.28). Conclusion Pessimistic explanatory style was associated with an increased risk of developing RA and increased mortality rate in patients with RA. PMID:28148754

Unmarked: An R package for fitting hierarchical models of wildlife occurrence and abundance

USGS Publications Warehouse

Fiske, I.J.; Chandler, R.B.

2011-01-01

Ecological research uses data collection techniques that are prone to substantial and unique types of measurement error to address scientic questions about species abundance and distribution. These data collection schemes include a number of survey methods in which unmarked individuals are counted, or determined to be present, at spatially- referenced sites. Examples include site occupancy sampling, repeated counts, distance sampling, removal sampling, and double observer sampling. To appropriately analyze these data, hierarchical models have been developed to separately model explanatory variables of both a latent abundance or occurrence process and a conditional detection process. Because these models have a straightforward interpretation paralleling mecha- nisms under which the data arose, they have recently gained immense popularity. The common hierarchical structure of these models is well-suited for a unied modeling in- terface. The R package unmarked provides such a unied modeling framework, including tools for data exploration, model tting, model criticism, post-hoc analysis, and model comparison.

Dynamical Systems Approach to Endothelial Heterogeneity

PubMed Central

Regan, Erzsébet Ravasz; Aird, William C.

2012-01-01

Rationale Objective Here we reexamine our current understanding of the molecular basis of endothelial heterogeneity. We introduce multistability as a new explanatory framework in vascular biology. Methods We draw on the field of non-linear dynamics to propose a dynamical systems framework for modeling multistability and its derivative properties, including robustness, memory, and plasticity. Conclusions Our perspective allows for both a conceptual and quantitative description of system-level features of endothelial regulation. PMID:22723222

Themes on circulation in the third world.

PubMed

Chapman, M; Prothero, R M

1983-01-01

"This article focuses upon circulation, or reciprocal flows of people, with specific reference to Third World societies." Aspects considered include attempts to standardize terminology and to formulate typologies of population movement; the development of explanatory models of circulation and modernization, social networks, family welfare, and capitalism; and "the transfer of methods and concepts to societies and populations different from those from which they initially evolved and in which they were first tested." excerpt

Explanatory Supplement to the Astronomical Almanac, Third Edition

NASA Astrophysics Data System (ADS)

Seidelmann, P. Kenneth; Urban, S. E.

2010-01-01

"The Explanatory Supplement to the Astronomical Almanac" (hereafter "The Explanatory Supplement") is a comprehensive reference book on the topic of positional astronomy, covering the theories and algorithms used to produce "The Astronomical Almanac" (AsA), an annual publication produced jointly by the Nautical Almanac Office of the US Naval Observatory (USNO) and Her Majesty's Nautical Almanac Office (HMNAO) of the UK Hydrographic Office. The first edition of The Explanatory Supplement appeared in 1961 and was reprinted with amendments during the 1970s. The second edition was printed in 1992 and reprinted until 2006. Since the second edition, several changes have taken place in positional astronomy regarding reference systems and internationally accepted models, data sets, and computational methods; these have been incorporated into the AsA. Additionally, the data presented in the AsA have been modified over the years, with new tables being added and some being discontinued. Given these changes, a new edition of The Explanatory Supplement is appropriate. The third edition has been in development for the last few years and will be available in 2010. The book is organized similarly to the second (1991) edition, with each chapter written by subject matter experts. Authors from USNO and HMNAO contributed to the majority of the book, but there are authors from Jet Propulsion Laboratory, Technical University of Dresden, National Geospatial-Intelligence Agency, University of Texas Austin, and University of Virginia. This paper will discuss this latest edition of the Explanatory Supplement.

The Social Explanatory Styles Questionnaire: Assessing Moderators of Basic Social-Cognitive Phenomena Including Spontaneous Trait Inference, the Fundamental Attribution Error, and Moral Blame

PubMed Central

Gill, Michael J.; Andreychik, Michael R.

2014-01-01

Why is he poor? Why is she failing academically? Why is he so generous? Why is she so conscientious? Answers to such everyday questions—social explanations—have powerful effects on relationships at the interpersonal and societal levels. How do people select an explanation in particular cases? We suggest that, often, explanations are selected based on the individual's pre-existing general theories of social causality. More specifically, we suggest that over time individuals develop general beliefs regarding the causes of social events. We refer to these beliefs as social explanatory styles. Our goal in the present article is to offer and validate a measure of individual differences in social explanatory styles. Accordingly, we offer the Social Explanatory Styles Questionnaire (SESQ), which measures three independent dimensions of social explanatory style: Dispositionism, historicism, and controllability. Studies 1–3 examine basic psychometric properties of the SESQ and provide positive evidence regarding internal consistency, factor structure, and both convergent and divergent validity. Studies 4–6 examine predictive validity for each subscale: Does each explanatory dimension moderate an important phenomenon of social cognition? Results suggest that they do. In Study 4, we show that SESQ dispositionism moderates the tendency to make spontaneous trait inferences. In Study 5, we show that SESQ historicism moderates the tendency to commit the Fundamental Attribution Error. Finally, in Study 6 we show that SESQ controllability predicts polarization of moral blame judgments: Heightened blaming toward controllable stigmas (assimilation), and attenuated blaming toward uncontrollable stigmas (contrast). Decades of research suggest that explanatory style regarding the self is a powerful predictor of self-functioning. We think it is likely that social explanatory styles—perhaps comprising interactive combinations of the basic dimensions tapped by the SESQ—will be similarly potent predictors of social functioning. We hope the SESQ will be a useful tool for exploring that possibility. PMID:25007152

The cognitive and affective structure of paranoid delusions: a transdiagnostic investigation of patients with schizophrenia spectrum disorders and depression.

PubMed

Bentall, Richard P; Rowse, Georgina; Shryane, Nick; Kinderman, Peter; Howard, Robert; Blackwood, Nigel; Moore, Rosie; Corcoran, Rhiannon

2009-03-01

Paranoid delusions are a common symptom of a range of psychotic disorders. A variety of psychological mechanisms have been implicated in their cause, including a tendency to jump to conclusions, an impairment in the ability to understand the mental states of other people (theory of mind), an abnormal anticipation of threat, and an abnormal explanatory style coupled with low self-esteem. To determine the structure of the relationships among psychological mechanisms contributing to paranoia in a transdiagnostic sample. Cross-sectional design, with relationships between predictor variables and paranoia examined by structural equation models with latent variables. Publicly funded psychiatric services in London and the North West of England. One hundred seventy-three patients with schizophrenia spectrum disorders, major depression, or late-onset schizophrenia-like psychosis, subdivided according to whether they were currently experiencing paranoid delusions. Sixty-four healthy control participants matched for appropriate demographic variables were included. Assessments of theory of mind, jumping to conclusions bias, and general intellectual functioning, with measures of threat anticipation, emotion, self-esteem, and explanatory style. The best fitting (chi(2)(96) = 131.69, P = .01; comparative fit index = 0.95; Tucker-Lewis Index = 0.96; root-mean-square error of approximation = 0.04) and most parsimonious model of the data indicated that paranoid delusions are associated with a combination of pessimistic thinking style (low self-esteem, pessimistic explanatory style, and negative emotion) and impaired cognitive performance (executive functioning, tendency to jump to conclusions, and ability to reason about the mental states of others). Pessimistic thinking correlated highly with paranoia even when controlling for cognitive performance (r = 0.65, P < .001), and cognitive performance correlated with paranoia when controlling for pessimism (r = -0.34, P < .001). Both cognitive and emotion-related processes are involved in paranoid delusions. Treatment for paranoid patients should address both types of processes.

High-sensitivity serum C-reactive protein levels in subjects with or without myocardial infarction or periodontitis.

PubMed

Persson, G Rutger; Pettersson, Thomas; Ohlsson, Ola; Renvert, Stefan

2005-03-01

Serum high-sensitivity C-reactive protein (hsC-rp) is a non-specific marker of inflammation. Elevated hsC-rp levels are found in subjects with cardiovascular diseases (CVDs). Periodontitis may influence hsC-rp levels. To assess periodontal status and hsC-rp serum levels in consecutive subjects hospitalized and diagnosed with acute myocardial infarction (AMI) (n=85) and in a group of carefully matched subjects (gender, age social, ethnic, and smoking habits) without clinical evidence of CVD (n=63). hsC-rp levels, other routine serum values, and clinical periodontal conditions were studied. Subjects with AMI had higher hsC-rp levels than control subjects (p<0.001, Mann-Whitney U-test). The odds that subjects in the control group with periodontitis (30% or more sites with>4.0 mm loss of alveolar bone) had serum hsC-rp>1.8 mg/l was 1.5 (95% CI: 1.1-7.3, p<0.05). Stepwise linear regression analysis failed to include periodontal parameters in an explanatory model to hsC-rp values. Only the serum leucocyte (white blood cell (WBC)) counts were explanatory to hsC-rp values (beta standard coefficient=0.45, t=3.2, p<0.001). Serum WBC counts were significantly higher in control subjects with periodontitis (p<0.03) but not in subjects in the AMI group (p<0.57). (1) As expected, elevated serum hsC-rp concentration and serum WBC counts are associated with acute coronary heart disease. (2) Elevated serum hsC-rp values are associated with radiographically defined periodontitis in subjects with no evidence of CVD. (3) Periodontal parameters are not explanatory to elevated serum hsC-rp values if serum WBC and low-density lipoprotein counts are included in the regression model. Copyright 2005 Blackwell Munksgaard.

Transportation economics and energy

NASA Astrophysics Data System (ADS)

Soltani Sobh, Ali

The overall objective of this research is to study the impacts of technology improvement including fuel efficiency increment, extending the use of natural gas vehicle and electric vehicles on key parameters of transportation. In the first chapter, a simple economic analysis is used in order to demonstrate the adoption rate of natural gas vehicles as an alternative fuel vehicle. The effect of different factors on adoption rate of commuters is calculated in sensitivity analysis. In second chapter the VMT is modeled and forecasted under influence of CNG vehicles in different scenarios. The VMT modeling is based on the time series data for Washington State. In order to investigate the effect of population growth on VMT, the per capita model is also developed. In third chapter the effect of fuel efficiency improvement on fuel tax revenue and greenhouse emission is examined. The model is developed based on time series data of Washington State. The rebound effect resulted from fuel efficiency improvement is estimated and is considered in fuel consumption forecasting. The reduction in fuel tax revenue and greenhouse gas (GHG) emissions as two outcomes of lower fuel consumption are computed. In addition, the proper fuel tax rate to restitute the revenue is suggested. In the fourth chapter effective factors on electric vehicles (EV) adoption is discussed. The constructed model is aggregated binomial logit share model that estimates the modal split between EV and conventional vehicles for different states over time. Various factors are incorporated in the utility function as explanatory variables in order to quantify their effect on EV adoption choices. The explanatory variables include income, VMT, electricity price, gasoline price, urban area and number of EV stations.

Multiple causes of nonstationarity in the Weihe annual low-flow series

NASA Astrophysics Data System (ADS)

Xiong, Bin; Xiong, Lihua; Chen, Jie; Xu, Chong-Yu; Li, Lingqi

2018-02-01

Under the background of global climate change and local anthropogenic activities, multiple driving forces have introduced various nonstationary components into low-flow series. This has led to a high demand on low-flow frequency analysis that considers nonstationary conditions for modeling. In this study, through a nonstationary frequency analysis framework with the generalized linear model (GLM) to consider time-varying distribution parameters, the multiple explanatory variables were incorporated to explain the variation in low-flow distribution parameters. These variables are comprised of the three indices of human activities (HAs; i.e., population, POP; irrigation area, IAR; and gross domestic product, GDP) and the eight measuring indices of the climate and catchment conditions (i.e., total precipitation P, mean frequency of precipitation events λ, temperature T, potential evapotranspiration (EP), climate aridity index AIEP, base-flow index (BFI), recession constant K and the recession-related aridity index AIK). This framework was applied to model the annual minimum flow series of both Huaxian and Xianyang gauging stations in the Weihe River, China (also known as the Wei He River). The results from stepwise regression for the optimal explanatory variables show that the variables related to irrigation, recession, temperature and precipitation play an important role in modeling. Specifically, analysis of annual minimum 30-day flow in Huaxian shows that the nonstationary distribution model with any one of all explanatory variables is better than the one without explanatory variables, the nonstationary gamma distribution model with four optimal variables is the best model and AIK is of the highest relative importance among these four variables, followed by IAR, BFI and AIEP. We conclude that the incorporation of multiple indices related to low-flow generation permits tracing various driving forces. The established link in nonstationary analysis will be beneficial to analyze future occurrences of low-flow extremes in similar areas.

Explanatory model of help-seeking and coping mechanisms among depressed women in three ethnic groups of Fars, Kurdish, and Turkish in Iran.

PubMed

Dejman, Masoumeh; Ekblad, Solvig; Forouzan, Ameneh-Setareh; Baradaran-Eftekhari, Monir; Malekafzali, Hossein

2008-07-01

As one of the most prevalent diseases globally and as an important cause of disability, depressive disorders are responsible for as many as one in every five visits to primary care doctors. Cultural variations in clinical presentation, sometimes make it difficult to recognize the disorder resulting in patients not being diagnosed and not receiving appropriate treatment. To address this issue, we conducted a qualitative pilot study on three ethnic groups including Fars, Kurdish, and Turkish in Iran to test the use of qualitative methods in exploring the explanatory models of help-seeking and coping with depression (without psychotic feature) among Iranian women. A qualitative study design was used based on an explanatory model of illness framework. Individual interviews were conducted with key informant (n=6), and depressed female patients (n=6). A hypothetical case vignette was also used in focus group discussions and individual interviews with lay people (three focus groups including 25 participants and six individual interviews; n=31). There were a few differences regarding help-seeking and coping mechanisms among the three ethnic groups studied. The most striking differences were in the area of treatment. Non-psychotic depressive disorder in all ethnicities was related to an external stressor, and symptoms of illness were viewed as a response to an event in the social world. Coping mechanisms involved two strategies: (1) solving problems by seeking social support from family and neighbors, religious practice, and engaging in pleasurable activities, and (2) seeking medical support from psychologists and family counselors. The Fars group was far more likely to recommend professional treatment and visiting psychiatrists whereas the other two ethnic groups (i.e., Turks and Kurds) preferred to consult family counselors, psychologists or other alternative care providers, and traditional healers. The study has educational and clinical implications. Cultural reframing of the patient's and family's perceptions about mental illness and depression may require community education. Family counseling, family therapy, and also religious practices can be used to empower the patient.

10 CFR Appendix I to Part 1050 - DOE Form 3735.2-Foreign Gifts Statement

Code of Federal Regulations, 2010 CFR

2010-01-01

... should always be indicated in item 1; if the employee is the recipient of the gift then items 5 and 6... information should be included in items 5 and 6. Item 2.Self explanatory. Items 3 and 4.The Office or Division... employee or a spouse or dependent. Items 5 and 6.See above, Item 1. Item 7.Self explanatory. Item 8.Self...

Developing deterioration models for Wyoming bridges.

DOT National Transportation Integrated Search

2016-05-01

Deterioration models for the Wyoming Bridge Inventory were developed using both stochastic and deterministic models. : The selection of explanatory variables is investigated and a new method using LASSO regression to eliminate human bias : in explana...

Family Interaction Patterns Associated with Self-Esteem in Preadolescent Girls and Boys.

ERIC Educational Resources Information Center

Loeb, Roger C.; And Others

1980-01-01

Examines four traditional explanatory models for the influence of parents on children's self-esteem. These models are directiveness, modeling, reward and punishment, and positive family interaction. (Author/DB)

Somatization revisited: diagnosis and perceived causes of common mental disorders.

PubMed

Henningsen, Peter; Jakobsen, Thorsten; Schiltenwolf, Marcus; Weiss, Mitchell G

2005-02-01

The assessment of somatoform disorders is complicated by persistent theoretical and practical questions of classification and assessment. Critical rethinking of professional concepts of somatization suggests the value of complementary assessment of patients' illness explanatory models of somatoform and other common mental disorders. We undertook this prospective study to assess medically unexplained somatic symptoms and their patient-perceived causes of illness and to show how patients' explanatory models relate to professional diagnoses of common mental disorders and how they may predict the short-term course of illness. Tertiary care patients (N=186) with prominent somatoform symptoms were evaluated with the Structured Clinical Interview for DSM-IV, a locally adapted Explanatory Model Interview to elicit patients' illness experience (priority symptoms) and perceived causes, and clinical self-report questionnaires. The self-report questionnaires were administered at baseline and after 6 months. Diagnostic overlap between somatoform, depressive, and anxiety disorders occurred frequently (79.6%). Patients explained pure somatoform disorders mainly with organic causal attributions; they explained pure depressive and/or anxiety disorders mainly with psychosocial perceived causes, and patients in the diagnostic overlap group typically reported mixed causal attributions. In this last group, among patients with similar levels of symptom severity, organic perceived causes were related to a lower physical health sum score on the MOS Short Form, and psychosocial perceived causes were related to less severe depressive symptoms, assessed with the Hospital Anxiety and Depression Scale at 6 months. Among patients meeting criteria for comorbid somatoform with anxiety and/or depressive disorders, complementary assessment of patient-perceived causes, a key element of illness explanatory models, was related to levels of functional impairment and short-term prognosis. For such patients, causal attributions may be particularly useful to clarify clinically significant features of common mental disorders and thereby contribute to clinical assessment.

Comparison between splines and fractional polynomials for multivariable model building with continuous covariates: a simulation study with continuous response.

PubMed

Binder, Harald; Sauerbrei, Willi; Royston, Patrick

2013-06-15

In observational studies, many continuous or categorical covariates may be related to an outcome. Various spline-based procedures or the multivariable fractional polynomial (MFP) procedure can be used to identify important variables and functional forms for continuous covariates. This is the main aim of an explanatory model, as opposed to a model only for prediction. The type of analysis often guides the complexity of the final model. Spline-based procedures and MFP have tuning parameters for choosing the required complexity. To compare model selection approaches, we perform a simulation study in the linear regression context based on a data structure intended to reflect realistic biomedical data. We vary the sample size, variance explained and complexity parameters for model selection. We consider 15 variables. A sample size of 200 (1000) and R(2)  = 0.2 (0.8) is the scenario with the smallest (largest) amount of information. For assessing performance, we consider prediction error, correct and incorrect inclusion of covariates, qualitative measures for judging selected functional forms and further novel criteria. From limited information, a suitable explanatory model cannot be obtained. Prediction performance from all types of models is similar. With a medium amount of information, MFP performs better than splines on several criteria. MFP better recovers simpler functions, whereas splines better recover more complex functions. For a large amount of information and no local structure, MFP and the spline procedures often select similar explanatory models. Copyright © 2012 John Wiley & Sons, Ltd.

Thinking about online sources: Exploring students' epistemic cognition in internet-based chemistry learning

NASA Astrophysics Data System (ADS)

Dai, Ting

This dissertation investigated the relation between epistemic cognition---epistemic aims and source beliefs---and learning outcome in an Internet--based research context. Based on a framework of epistemic cognition (Chinn, Buckland, & Samarapungavan, 2011), a context--specific epistemic aims and source beliefs questionnaire (CEASBQ) was developed and administered to 354 students from college--level introductory chemistry courses. A series of multitrait--multimethod model comparisons provided evidence for construct convergent and discriminant validity for three epistemic aims--- true beliefs, justified beliefs, explanatory connection, which were all distinguished from, yet correlated with, mastery goals. Students' epistemic aims were specific to the chemistry topics in research. Multidimensional scaling results indicated that students' source evaluation was based on two dimensions--- professional expertise and first--hand knowledge, suggesting a multidimensional structure of source beliefs. Most importantly, online learning outcome was found to be significantly associated with two epistemic aims---justified beliefs and explanatory connection: The more students sought justifications in the online research, the lower they tended to score on the learning outcome measure, whereas the more students sought explanatory connections between information, the higher they scored on the outcome measure. There was a significant but small positive association between source beliefs and learning outcome. The influences of epistemic aims and source beliefs on learning outcome were found to be above and beyond the effects of a number of covariates, including prior knowledge and perceived ability with online sources.

Performance of Comorbidity, Risk Adjustment, and Functional Status Measures in Expenditure Prediction for Patients With Diabetes

PubMed Central

Maciejewski, Matthew L.; Liu, Chuan-Fen; Fihn, Stephan D.

2009-01-01

OBJECTIVE—To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes. RESEARCH DESIGN AND METHODS—This study included a retrospective cohort of 3,092 diabetic veterans participating in a multisite trial. Two comorbidity measures, four risk adjusters, a functional status measure, a diabetes complication count, and baseline expenditures were constructed from administrative and survey data. Outpatient, inpatient, and total expenditure models were estimated using ordinary least squares regression. Adjusted R2 statistics and predictive ratios were compared across measures to assess overall explanatory power and explanatory power of low- and high-cost subgroups. RESULTS—Administrative data–based risk adjusters performed better than the comorbidity, functional status, and diabetes-specific measures in all expenditure models. The diagnostic cost groups (DCGs) measure had the greatest predictive power overall and for the low- and high-cost subgroups, while the diabetes-specific measure had the lowest predictive power. A model with DCGs and the diabetes-specific measure modestly improved predictive power. CONCLUSIONS—Existing generic measures can be useful for diabetes-specific research and policy applications, but more predictive diabetes-specific measures are needed. PMID:18945927

Variations in non-prescription drug consumption and expenditure: Determinants and policy implications.

PubMed

Otto, Monica; Armeni, Patrizio; Jommi, Claudio

2018-01-31

This paper analyses the determinants of cross-regional variations in expenditure and consumption for non-prescription drugs using the Italian Health Care Service as a case study. This research question has never been posed in other literature contributions. Per capita income, the incidence of elderly people, the presence of distribution points alternative to community pharmacies (para-pharmacies and drug corners in supermarkets), and the disease prevalence were included as possible explanatory variables. A trade-off between consumption of non-prescription and prescription-only drugs was also investigated. Correlation was tested through linear regression models with regional fixed-effects. Demand-driven variables, including the prevalence of the target diseases and income, were found to be more influential than supply-side variables, such as the presence of alternative distribution points. Hence, the consumption of non-prescription drugs appears to respond to needs and is not induced by the supply. The expected trade-off between consumption for prescription-only and non-prescription drugs was not empirically found: increasing the use of non-prescription drugs did not automatically imply savings on prescription-only drugs covered by third payers. Despite some caveats (the short period of time covered by the longitudinal data and some missing monthly data), the regression model revealed a high explanatory power of the variability and a strong predictive ability of future values. Copyright © 2018 Elsevier B.V. All rights reserved.

Forecasting the use of elderly care: a static micro-simulation model.

PubMed

Eggink, Evelien; Woittiez, Isolde; Ras, Michiel

2016-07-01

This paper describes a model suitable for forecasting the use of publicly funded long-term elderly care, taking into account both ageing and changes in the health status of the population. In addition, the impact of socioeconomic factors on care use is included in the forecasts. The model is also suitable for the simulation of possible implications of some specific policy measures. The model is a static micro-simulation model, consisting of an explanatory model and a population model. The explanatory model statistically relates care use to individual characteristics. The population model mimics the composition of the population at future points in time. The forecasts of care use are driven by changes in the composition of the population in terms of relevant characteristics instead of dynamics at the individual level. The results show that a further 37 % increase in the use of elderly care (from 7 to 9 % of the Dutch 30-plus population) between 2008 and 2030 can be expected due to a further ageing of the population. However, the use of care is expected to increase less than if it were based on the increasing number of elderly only (+70 %), due to decreasing disability levels and increasing levels of education. As an application of the model, we simulated the effects of restricting access to residential care to elderly people with severe physical disabilities. The result was a lower growth of residential care use (32 % instead of 57 %), but a somewhat faster growth in the use of home care (35 % instead of 32 %).

Models, theory structure and mechanisms in biochemistry: The case of allosterism.

PubMed

Alleva, Karina; Díez, José; Federico, Lucia

2017-06-01

From the perspective of the new mechanistic philosophy, it has been argued that explanatory causal mechanisms in some special sciences such as biochemistry and neurobiology cannot be captured by any useful notion of theory, or at least by any standard notion. The goal of this paper is to show that a model-theoretic notion of theory, and in particular the structuralist notion of a theory-net already applied to other unified explanatory theories, adequately suits the MWC allosteric mechanism explanatory set-up. We also argue, contra some mechanistic claims questioning the use of laws in biological explanations, that the theory reconstructed in this way essentially contains non-accidental regularities that qualify as laws, and that taking into account these lawful components, it is possible to explicate the unified character of the theory. Finally, we argue that, contrary to what some mechanists also claim, functional explanations that do not fully specify the mechanistic structure are not defective or incomplete in any relevant sense, and that functional components are perfectly explanatory. The conclusion is that, as some authors have emphasized in other fields (Walmsley 2008), particular elements of traditional approaches do not contradict but rather complement the new mechanist philosophy, and taken together they may offer a more complete understanding of special sciences and the variety of explanations they provide. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Mole as an Explanatory Device: How Do You Know a Mole if You See One? A Manual for Chemistry Students. Sample Teaching Materials: The Explanatory Modes Project.

ERIC Educational Resources Information Center

Roberts, Douglas A.

This booklet is designed to supplement the study of introductory chemistry. It deals particularly with the mole concept but also includes ideas for analyzing the kinds of statements that appear in all science textbooks and scientific writing. The material in the booklet should be studied after the completion of an introductory textbook study of…

The evolutionary interplay of intergroup conflict and altruism in humans: a review of parochial altruism theory and prospects for its extension

PubMed Central

Rusch, Hannes

2014-01-01

Drawing on an idea proposed by Darwin, it has recently been hypothesized that violent intergroup conflict might have played a substantial role in the evolution of human cooperativeness and altruism. The central notion of this argument, dubbed ‘parochial altruism’, is that the two genetic or cultural traits, aggressiveness against the out-groups and cooperativeness towards the in-group, including self-sacrificial altruistic behaviour, might have coevolved in humans. This review assesses the explanatory power of current theories of ‘parochial altruism’. After a brief synopsis of the existing literature, two pitfalls in the interpretation of the most widely used models are discussed: potential direct benefits and high relatedness between group members implicitly induced by assumptions about conflict structure and frequency. Then, a number of simplifying assumptions made in the construction of these models are pointed out which currently limit their explanatory power. Next, relevant empirical evidence from several disciplines which could guide future theoretical extensions is reviewed. Finally, selected alternative accounts of evolutionary links between intergroup conflict and intragroup cooperation are briefly discussed which could be integrated with parochial altruism in the future. PMID:25253457

Detection of outliers in the response and explanatory variables of the simple circular regression model

NASA Astrophysics Data System (ADS)

Mahmood, Ehab A.; Rana, Sohel; Hussin, Abdul Ghapor; Midi, Habshah

2016-06-01

The circular regression model may contain one or more data points which appear to be peculiar or inconsistent with the main part of the model. This may be occur due to recording errors, sudden short events, sampling under abnormal conditions etc. The existence of these data points "outliers" in the data set cause lot of problems in the research results and the conclusions. Therefore, we should identify them before applying statistical analysis. In this article, we aim to propose a statistic to identify outliers in the both of the response and explanatory variables of the simple circular regression model. Our proposed statistic is robust circular distance RCDxy and it is justified by the three robust measurements such as proportion of detection outliers, masking and swamping rates.

Explanatory model of emotional-cognitive variables in school mathematics performance: a longitudinal study in primary school

PubMed Central

Cerda, Gamal; Pérez, Carlos; Navarro, José I.; Aguilar, Manuel; Casas, José A.; Aragón, Estíbaliz

2015-01-01

This study tested a structural model of cognitive-emotional explanatory variables to explain performance in mathematics. The predictor variables assessed were related to students’ level of development of early mathematical competencies (EMCs), specifically, relational and numerical competencies, predisposition toward mathematics, and the level of logical intelligence in a population of primary school Chilean students (n = 634). This longitudinal study also included the academic performance of the students during a period of 4 years as a variable. The sampled students were initially assessed by means of an Early Numeracy Test, and, subsequently, they were administered a Likert-type scale to measure their predisposition toward mathematics (EPMAT) and a basic test of logical intelligence. The results of these tests were used to analyse the interaction of all the aforementioned variables by means of a structural equations model. This combined interaction model was able to predict 64.3% of the variability of observed performance. Preschool students’ performance in EMCs was a strong predictor for achievement in mathematics for students between 8 and 11 years of age. Therefore, this paper highlights the importance of EMCs and the modulating role of predisposition toward mathematics. Also, this paper discusses the educational role of these findings, as well as possible ways to improve negative predispositions toward mathematical tasks in the school domain. PMID:26441739

"And I think that we can fix it": mental models used in high-risk surgical decision making.

PubMed

Kruser, Jacqueline M; Pecanac, Kristen E; Brasel, Karen J; Cooper, Zara; Steffens, Nicole M; McKneally, Martin F; Schwarze, Margaret L

2015-04-01

To examine how surgeons use the "fix-it" model to communicate with patients before high-risk operations. The "fix-it" model characterizes disease as an isolated abnormality that can be restored to normal form and function through medical intervention. This mental model is familiar to patients and physicians, but it is ineffective for chronic conditions and treatments that cannot achieve normalcy. Overuse may lead to permissive decision making favoring intervention. Efforts to improve surgical decision making will need to consider how mental models function in clinical practice, including "fix-it." We observed surgeons who routinely perform high-risk surgery during preoperative discussions with patients. We used qualitative content analysis to explore the use of "fix-it" in 48 audio-recorded conversations. Surgeons used the "fix-it" model for 2 separate purposes during preoperative conversations: (1) as an explanatory tool to facilitate patient understanding of disease and surgery, and (2) as a deliberation framework to assist in decision making. Although surgeons commonly used "fix-it" as an explanatory model, surgeons explicitly discussed limitations of the "fix-it" model as an independent rationale for operating as they deliberated about the value of surgery. Although the use of "fix-it" is familiar for explaining medical information to patients, surgeons recognize that the model can be problematic for determining the value of an operation. Whether patients can transition between understanding how their disease is fixed with surgery to a subsequent deliberation about whether they should have surgery is unclear and may have broader implications for surgical decision making.

Modeling and Forecasting Mortality With Economic Growth: A Multipopulation Approach.

PubMed

Boonen, Tim J; Li, Hong

2017-10-01

Research on mortality modeling of multiple populations focuses mainly on extrapolating past mortality trends and summarizing these trends by one or more common latent factors. This article proposes a multipopulation stochastic mortality model that uses the explanatory power of economic growth. In particular, we extend the Li and Lee model (Li and Lee 2005) by including economic growth, represented by the real gross domestic product (GDP) per capita, to capture the common mortality trend for a group of populations with similar socioeconomic conditions. We find that our proposed model provides a better in-sample fit and an out-of-sample forecast performance. Moreover, it generates lower (higher) forecasted period life expectancy for countries with high (low) GDP per capita than the Li and Lee model.

The self, attributional processes and abnormal beliefs: towards a model of persecutory delusions.

PubMed

Bentall, R P; Kinderman, P; Kaney, S

1994-03-01

In this paper we review a series of recent investigations into cognitive abnormalities associated with persecutory delusions. Studies indicate that persecutory delusions are associated with abnormal attention to threat-related stimuli, an explanatory bias towards attributing negative outcomes to external causes and biases in information processing relating to the self-concept. We propose an integrative model to account for these findings in which it is hypothesized that, in deluded patients, activation of self/ideal discrepancies by threat-related information triggers defensive explanatory biases, which have the function of reducing the self/ideal discrepancies but result in persecutory ideation. We conclude by discussing the implications of this model for the cognitive-behavioural treatment of paranoid delusions.

Parental explanatory models of ADHD: gender and cultural variations.

PubMed

Bussing, Regina; Gary, Faye A; Mills, Terry L; Garvan, Cynthia Wilson

2003-10-01

This study describes parents' explanatory models of Attention Deficit Hyperactivity Disorder (ADHD) and examines model variation by child characteristics. Children with ADHD (N = 182) were identified from a school district population of elementary school students. A reliable coding system was developed for parental responses obtained in ethnographic interviews in order to convert qualitative into numerical data for quantitative analysis. African-American parents were less likely to connect the school system to ADHD problem identification, expressed fewer worries about ADHD-related school problems, and voiced fewer preferences for school interventions than Caucasian parents, pointing to a potential disconnect with the school system. More African-American than Caucasian parents were unsure about potential causes of and treatments for ADHD, indicating a need for culturally appropriate parent education approaches.

Some methodological issues in the longitudinal analysis of demographic data.

PubMed

Krishinan, P

1982-12-01

Most demographic data are macro (or aggregate) in nature. Some relevant methodological issues are presented here in a time series study using aggregate data. The micro-macro distinction is relative. Time enters into the micro and macro variables in different ways. A simple micro model of rural-urban migration is given. Method 1 is to assume homogeneity in behavior. Method 2 is a Bayesian estimation. A discusssion of the results follows. Time series models of aggregate data are given. The nature of the model--predictive or explanatory--must be decided on. Explanatory models in longitudinal studies have been developed. Ways to go to the micro level from the macro are discussed. The aggregation-disaggregation problem in demography is not similar to that in econometrics. To understand small populations, separate micro level data have to be collected and analyzed and appropriate models developed. Both types of models have their uses.

Testing an explanatory model of nurses' intention to report adverse drug reactions in hospital settings.

PubMed

Angelis, Alessia De; Pancani, Luca; Steca, Patrizia; Colaceci, Sofia; Giusti, Angela; Tibaldi, Laura; Alvaro, Rosaria; Ausili, Davide; Vellone, Ercole

2017-05-01

To test an explanatory model of nurses' intention to report adverse drug reactions in hospital settings, based on the theory of planned behaviour. Under-reporting of adverse drug reactions is an important problem among nurses. A cross-sectional design was used. Data were collected with the adverse drug reporting nurses' questionnaire. Confirmatory factor analysis was performed to test the factor validity of the adverse drug reporting nurses' questionnaire, and structural equation modelling was used to test the explanatory model. The convenience sample comprised 500 Italian hospital nurses (mean age = 43.52). Confirmatory factor analysis supported the factor validity of the adverse drug reporting nurses' questionnaire. The structural equation modelling showed a good fit with the data. Nurses' intention to report adverse drug reactions was significantly predicted by attitudes, subjective norms and perceived behavioural control (R² = 0.16). The theory of planned behaviour effectively explained the mechanisms behind nurses' intention to report adverse drug reactions, showing how several factors come into play. In a scenario of organisational empowerment towards adverse drug reaction reporting, the major predictors of the intention to report are support for the decision to report adverse drug reactions from other health care practitioners, perceptions about the value of adverse drug reaction reporting and nurses' favourable self-assessment of their adverse drug reaction reporting skills. © 2017 John Wiley & Sons Ltd.

Revising explanatory models to accommodate anomalous genetic phenomena: Problem solving in the context of discovery

NASA Astrophysics Data System (ADS)

Hafner, Robert; Stewart, Jim

Past problem-solving research has provided a basis for helping students structure their knowledge and apply appropriate problem-solving strategies to solve problems for which their knowledge (or mental models) of scientific phenomena is adequate (model-using problem solving). This research examines how problem solving in the domain of Mendelian genetics proceeds in situations where solvers' mental models are insufficient to solve problems at hand (model-revising problem solving). Such situations require solvers to use existing models to recognize anomalous data and to revise those models to accommodate the data. The study was conducted in the context of 9-week high school genetics course and addressed: the heuristics charactenstic of successful model-revising problem solving: the nature of the model revisions, made by students as well as the nature of model development across problem types; and the basis upon which solvers decide that a revised model is sufficient (that t has both predictive and explanatory power).

Silent strain of caregiving: exploring the best predictors of distress in family carers of geriatric patients.

PubMed

Bień-Barkowska, Katarzyna; Doroszkiewicz, Halina; Bień, Barbara

2017-01-01

The aim of this article was to identify the best predictors of distress suffered by family carers (FCs) of geriatric patients. A cross-sectional study of 100 FC-geriatric patient dyads was conducted. The negative impact of care (NIoC) subscale of the COPE index was dichotomized to identify lower stress (score of ≤15 on the scale) and higher stress (score of ≥16 on the scale) exerted on FCs by the process of providing care. The set of explanatory variables comprised a wide range of sociodemographic and care-related attributes, including patient-related results from comprehensive geriatric assessments and disease profiles. The best combination of explanatory variables that provided the highest predictive power for distress among FCs in the multiple logistic regression (LR) model was determined according to statistical information criteria. The statistical robustness of the observed relationships and the discriminative power of the model were verified with the cross-validation method. The mean age of FCs was 57.2 (±10.6) years, whereas that of geriatric patients was 81.7 (±6.4) years. Despite the broad initial set of potential explanatory variables, only five predictors were jointly selected for the best statistical model. A higher level of distress was independently predicted by lower self-evaluation of health; worse self-appraisal of coping well as a caregiver; lower sense of general support; more hours of care per week; and the motor retardation of the cared-for person measured with the speed of the Timed Up and Go (TUG) test. Worse performance on the TUG test was only the patient-related predictor of distress among the variables examined as contributors to the higher NIoC. Enhancing the mobility of geriatric patients through suitably tailored kinesitherapeutic methods during their hospital stay may mitigate the burden endured by FCs.

'A chronic disease is a disease which keeps coming back…it is like the flu': chronic disease risk perception and explanatory models among French- and Swahili-speaking African migrants.

PubMed

Cooper, Maxwell; Harding, Seeromanie; Mullen, Kenneth; O'Donnell, Catherine

2012-01-01

African migrants to the West are at increased risk of hypertensive related diseases and certain cancers compared with other ethnic groups. Little is known about their awareness of this risk or knowledge of associated risk factors. To explore African migrants' perceptions of chronic disease risk, risk factors and underlying explanatory models. In-depth interviews with 19 Africans from French- or Swahili-speaking countries living in Glasgow were conducted. Interviews were transcribed and 10 translated (3 Swahili and 7 French). Analysis was informed by a grounded theory approach. Narratives suggested low awareness of chronic disease risk among participants. Africans reported a positive outlook on life that discouraged thought about future sickness. Infectious diseases were considered the dominant health threat for African migrants, mainly HIV but also TB and 'flu'. Chronic diseases were sometimes described as contagious. Explanatory models of chronic disease included bodily/dietary imbalance, stress/exertion, heredity/predisposition and food contamination. Cancer was feared but not considered a major threat. Cancer was considered more common in Europe than Africa and attributed to chemical contamination from fertilisers, food preservatives and industrial pollution. Evidence cited for these chemicals was rapid livestock/vegetable production, large size of livestock (e.g., fish), softness of meat and flavourless food. Chemicals were reported to circulate silently inside the body and cancer to form in the part where they deposit, sometimes years later. Cardiovascular diseases were described in terms of acute symptoms that required short-term medication. Confidentiality concerns were reported to prevent discussion of chronic disease between Africans. This study suggests a need to improve chronic disease health literacy among African migrants to promote engagement with preventive behaviours. This should build on not only participants' existing knowledge of disease causation and risk factors but also their self-reliance in the pursuit of a healthy lifestyle and desire to retain cultural knowledge and practice.

[Associations of the Employment Status during the First 2 Years Following Medical Rehabilitation and Long Term Occupational Trajectories: Implications for Outcome Measurement].

PubMed

Holstiege, J; Kaluscha, R; Jankowiak, S; Krischak, G

2017-02-01

Study Objectives: The aim was to investigate the predictive value of the employment status measured in the 6 th , 12 th , 18 th and 24 th month after medical rehabilitation for long-term employment trajectories during 4 years. Methods: A retrospective study was conducted based on a 20%-sample of all patients receiving inpatient rehabilitation funded by the German pension fund. Patients aged <62 years who were treated due to musculoskeletal, cardiovascular or psychosomatic disorders during the years 2002-2005 were included and followed for 4 consecutive years. The predictive value of the employment status in 4 predefined months after discharge (6 th , 12 th , 18 th and 24 th month), for the total number of months in employment in 4 years following rehabilitative treatment was analyzed using multiple linear regression. Per time point, separate regression analyses were conducted, including the employment status (employed vs. unemployed) at the respective point in time as explanatory variable, besides a standard set of additional prognostic variables. Results: A total of 252 591 patients were eligible for study inclusion. The level of explained variance of the regression models increased with the point in time used to measure the employment status, included as explanatory variable. Overall the R²-measure increased by 30% from the regression model that included the employment status in the 6 th month (R²=0.60) to the model that included the work status in the 24 th month (R²=0.78). Conclusion: The degree of accuracy in the prognosis of long-term employment biographies increases with the point in time used to measure employment in the first 2 years following rehabilitation. These findings should be taken into consideration for the predefinition of time points used to measure the employment status in future studies. © Georg Thieme Verlag KG Stuttgart · New York.

Hypertension in the very old; prevalence, awareness, treatment and control: a cross-sectional population-based study in a Spanish municipality.

PubMed

Aguado, Alba; López, Flora; Miravet, Sonia; Oriol, Pilar; Fuentes, M Isabel; Henares, Belén; Badia, Teresa; Esteve, Lluis; Peligro, Javier

2009-05-08

Information on hypertension in the very elderly is sparse. Until recently evidence of benefits from pharmacological treatment was inconclusive. We estimated the prevalence of hypertension in subjects aged 80 or more, the proportion of awareness, treatment and control. Explanatory variables associated with good control were also studied. Cross sectional, population-based study, conducted in Martorell, an urban Spanish municipality, in 2005. By simple random sampling from the census, 323 subjects aged 80 or more were included. Patients were visited at home or in the geriatric institution and after giving informed consent, the study variables were collected. These included: supine and standing blood pressure and information about diagnosis and treatment of hypertension. The estimation and 95% confidence interval were obtained and a logistic regression model was used to study explanatory variables associated with blood pressure below 140/90 mm Hg. The prevalence of hypertension was 72.8% (95%CI: 69.5-76.6%) and 93% of the patients were aware of this condition, of whom 96.3% (95%CI: 93.65-97.9%) had been prescribed pharmacological treatment and 30.7% (95%CI: 25.8 - 36.1%) had blood pressure below 140/90 mm Hg. Some of the patients (43%) had one antihypertensive drug and 39.5% had two in combination. Explanatory variables associated with blood pressure below 140/90 mm Hg included prescription of a diuretic, OR: 0.31 (95%CI: 0.14-0.66), and history of ischemic heart disease, OR: 0.21 (95%CI: 0.1-0.47). The prevalence of hypertension in population aged 80 or more was over 70%. Most patients were aware of this condition and they had antihypertensive medication prescribed. Approximately one third of treated patients had blood pressure below 140/90 mm Hg. Patients with heart disease and with diuretics had more frequently blood pressure below this value.

Hypertension in the very old; prevalence, awareness, treatment and control: a cross-sectional population-based study in a Spanish municipality

PubMed Central

Aguado, Alba; López, Flora; Miravet, Sonia; Oriol, Pilar; Fuentes, M Isabel; Henares, Belén; Badia, Teresa; Esteve, Lluis; Peligro, Javier

2009-01-01

Background Information on hypertension in the very elderly is sparse. Until recently evidence of benefits from pharmacological treatment was inconclusive. We estimated the prevalence of hypertension in subjects aged 80 or more, the proportion of awareness, treatment and control. Explanatory variables associated with good control were also studied. Methods Cross sectional, population-based study, conducted in Martorell, an urban Spanish municipality, in 2005. By simple random sampling from the census, 323 subjects aged 80 or more were included. Patients were visited at home or in the geriatric institution and after giving informed consent, the study variables were collected. These included: supine and standing blood pressure and information about diagnosis and treatment of hypertension. The estimation and 95% confidence interval were obtained and a logistic regression model was used to study explanatory variables associated with blood pressure below 140/90 mm Hg. Results The prevalence of hypertension was 72.8% (95%CI: 69.5 – 76.6%) and 93% of the patients were aware of this condition, of whom 96.3% (95%CI: 93.65 – 97.9%) had been prescribed pharmacological treatment and 30.7% (95%CI: 25.8 – 36.1%) had blood pressure below 140/90 mm Hg. Some of the patients (43%) had one antihypertensive drug and 39.5% had two in combination. Explanatory variables associated with blood pressure below 140/90 mm Hg included prescription of a diuretic, OR: 0.31 (95%CI: 0.14 – 0.66), and history of ischemic heart disease, OR: 0.21 (95%CI: 0.1 – 0.47). Conclusion The prevalence of hypertension in population aged 80 or more was over 70%. Most patients were aware of this condition and they had antihypertensive medication prescribed. Approximately one third of treated patients had blood pressure below 140/90 mm Hg. Patients with heart disease and with diuretics had more frequently blood pressure below this value. PMID:19426484

An Explanatory Model of Dating Violence Risk Factors in Spanish Adolescents.

PubMed

Aizpitarte, Alazne; Alonso-Arbiol, Itziar; Van de Vijver, Fons J R

2017-12-01

Dating violence is a serious public health issue that needs further understanding in terms of risk factors that may be involved in it. The main goal of this study was to test a mediational model of dating violence risk factors. The sample was composed of 477 secondary and college students from Spain (59% females). A dynamic developmental explanatory model considering aggressiveness, insecure attachment, interparental conflict, and peer dating violence was tested using a multigroup structural equation model. Aggressiveness partially mediated the relation between anxious attachment and dating violence and fully mediated the association between interparental conflict resolution and dating violence. Furthermore, perceived peer dating violence was a direct predictor of dating violence. Implications for prevention and intervention plans are discussed. © 2017 The Authors. Journal of Research on Adolescence © 2017 Society for Research on Adolescence.

A comparison of data-driven groundwater vulnerability assessment methods

USGS Publications Warehouse

Sorichetta, Alessandro; Ballabio, Cristiano; Masetti, Marco; Robinson, Gilpin R.; Sterlacchini, Simone

2013-01-01

Increasing availability of geo-environmental data has promoted the use of statistical methods to assess groundwater vulnerability. Nitrate is a widespread anthropogenic contaminant in groundwater and its occurrence can be used to identify aquifer settings vulnerable to contamination. In this study, multivariate Weights of Evidence (WofE) and Logistic Regression (LR) methods, where the response variable is binary, were used to evaluate the role and importance of a number of explanatory variables associated with nitrate sources and occurrence in groundwater in the Milan District (central part of the Po Plain, Italy). The results of these models have been used to map the spatial variation of groundwater vulnerability to nitrate in the region, and we compare the similarities and differences of their spatial patterns and associated explanatory variables. We modify the standard WofE method used in previous groundwater vulnerability studies to a form analogous to that used in LR; this provides a framework to compare the results of both models and reduces the effect of sampling bias on the results of the standard WofE model. In addition, a nonlinear Generalized Additive Model has been used to extend the LR analysis. Both approaches improved discrimination of the standard WofE and LR models, as measured by the c-statistic. Groundwater vulnerability probability outputs, based on rank-order classification of the respective model results, were similar in spatial patterns and identified similar strong explanatory variables associated with nitrate source (population density as a proxy for sewage systems and septic sources) and nitrate occurrence (groundwater depth).

Prediction equations of forced oscillation technique: the insidious role of collinearity.

PubMed

Narchi, Hassib; AlBlooshi, Afaf

2018-03-27

Many studies have reported reference data for forced oscillation technique (FOT) in healthy children. The prediction equation of FOT parameters were derived from a multivariable regression model examining the effect of age, gender, weight and height on each parameter. As many of these variables are likely to be correlated, collinearity might have affected the accuracy of the model, potentially resulting in misleading, erroneous or difficult to interpret conclusions.The aim of this work was: To review all FOT publications in children since 2005 to analyze whether collinearity was considered in the construction of the published prediction equations. Then to compare these prediction equations with our own study. And to analyse, in our study, how collinearity between the explanatory variables might affect the predicted equations if it was not considered in the model. The results showed that none of the ten reviewed studies had stated whether collinearity was checked for. Half of the reports had also included in their equations variables which are physiologically correlated, such as age, weight and height. The predicted resistance varied by up to 28% amongst these studies. And in our study, multicollinearity was identified between the explanatory variables initially considered for the regression model (age, weight and height). Ignoring it would have resulted in inaccuracies in the coefficients of the equation, their signs (positive or negative), their 95% confidence intervals, their significance level and the model goodness of fit. In Conclusion with inaccurately constructed and improperly reported models, understanding the results and reproducing the models for future research might be compromised.

A hierarchical spatial model of avian abundance with application to Cerulean Warblers

USGS Publications Warehouse

Thogmartin, Wayne E.; Sauer, John R.; Knutson, Melinda G.

2004-01-01

Surveys collecting count data are the primary means by which abundance is indexed for birds. These counts are confounded, however, by nuisance effects including observer effects and spatial correlation between counts. Current methods poorly accommodate both observer and spatial effects because modeling these spatially autocorrelated counts within a hierarchical framework is not practical using standard statistical approaches. We propose a Bayesian approach to this problem and provide as an example of its implementation a spatial model of predicted abundance for the Cerulean Warbler (Dendroica cerulea) in the Prairie-Hardwood Transition of the upper midwestern United States. We used an overdispersed Poisson regression with fixed and random effects, fitted by Markov chain Monte Carlo methods. We used 21 years of North American Breeding Bird Survey counts as the response in a loglinear function of explanatory variables describing habitat, spatial relatedness, year effects, and observer effects. The model included a conditional autoregressive term representing potential correlation between adjacent route counts. Categories of explanatory habitat variables in the model included land cover composition and configuration, climate, terrain heterogeneity, and human influence. The inherent hierarchy in the model was from counts occurring, in part, as a function of observers within survey routes within years. We found that the percentage of forested wetlands, an index of wetness potential, and an interaction between mean annual precipitation and deciduous forest patch size best described Cerulean Warbler abundance. Based on a map of relative abundance derived from the posterior parameter estimates, we estimated that only 15% of the species' population occurred on federal land, necessitating active engagement of public landowners and state agencies in the conservation of the breeding habitat for this species. Models of this type can be applied to any data in which the response is counts, such as animal counts, activity (e.g.,nest) counts, or species richness. The most noteworthy practical application of this spatial modeling approach is the ability to map relative species abundance. The functional relationships that we elucidated for the Cerulean Warbler provide a basis for the development of management programs and may serve to focus management and monitoring on areas and habitat variables important to Cerulean Warblers.

Acute care patient portals: a qualitative study of stakeholder perspectives on current practices.

PubMed

Collins, Sarah A; Rozenblum, Ronen; Leung, Wai Yin; Morrison, Constance Rc; Stade, Diana L; McNally, Kelly; Bourie, Patricia Q; Massaro, Anthony; Bokser, Seth; Dwyer, Cindy; Greysen, Ryan S; Agarwal, Priyanka; Thornton, Kevin; Dalal, Anuj K

2017-04-01

To describe current practices and stakeholder perspectives of patient portals in the acute care setting. We aimed to: (1) identify key features, (2) recognize challenges, (3) understand current practices for design, configuration, and use, and (4) propose new directions for investigation and innovation. Mixed methods including surveys, interviews, focus groups, and site visits with stakeholders at leading academic medical centers. Thematic analyses to inform development of an explanatory model and recommendations. Site surveys were administered to 5 institutions. Thirty interviews/focus groups were conducted at 4 site visits that included a total of 84 participants. Ten themes regarding content and functionality, engagement and culture, and access and security were identified, from which an explanatory model of current practices was developed. Key features included clinical data, messaging, glossary, patient education, patient personalization and family engagement tools, and tiered displays. Four actionable recommendations were identified by group consensus. Design, development, and implementation of acute care patient portals should consider: (1) providing a single integrated experience across care settings, (2) humanizing the patient-clinician relationship via personalization tools, (3) providing equitable access, and (4) creating a clear organizational mission and strategy to achieve outcomes of interest. Portals should provide a single integrated experience across the inpatient and ambulatory settings. Core functionality includes tools that facilitate communication, personalize the patient, and deliver education to advance safe, coordinated, and dignified patient-centered care. Our findings can be used to inform a "road map" for future work related to acute care patient portals. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

On the predictive ability of mechanistic models for the Haitian cholera epidemic.

PubMed

Mari, Lorenzo; Bertuzzo, Enrico; Finger, Flavio; Casagrandi, Renato; Gatto, Marino; Rinaldo, Andrea

2015-03-06

Predictive models of epidemic cholera need to resolve at suitable aggregation levels spatial data pertaining to local communities, epidemiological records, hydrologic drivers, waterways, patterns of human mobility and proxies of exposure rates. We address the above issue in a formal model comparison framework and provide a quantitative assessment of the explanatory and predictive abilities of various model settings with different spatial aggregation levels and coupling mechanisms. Reference is made to records of the recent Haiti cholera epidemics. Our intensive computations and objective model comparisons show that spatially explicit models accounting for spatial connections have better explanatory power than spatially disconnected ones for short-to-intermediate calibration windows, while parsimonious, spatially disconnected models perform better with long training sets. On average, spatially connected models show better predictive ability than disconnected ones. We suggest limits and validity of the various approaches and discuss the pathway towards the development of case-specific predictive tools in the context of emergency management. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Bayesian dynamical systems modelling in the social sciences.

PubMed

Ranganathan, Shyam; Spaiser, Viktoria; Mann, Richard P; Sumpter, David J T

2014-01-01

Data arising from social systems is often highly complex, involving non-linear relationships between the macro-level variables that characterize these systems. We present a method for analyzing this type of longitudinal or panel data using differential equations. We identify the best non-linear functions that capture interactions between variables, employing Bayes factor to decide how many interaction terms should be included in the model. This method punishes overly complicated models and identifies models with the most explanatory power. We illustrate our approach on the classic example of relating democracy and economic growth, identifying non-linear relationships between these two variables. We show how multiple variables and variable lags can be accounted for and provide a toolbox in R to implement our approach.

A Predictive Model of Domestic Violence in Multicultural Families Focusing on Perpetrator.

PubMed

Choi, Eun Young; Hyun, Hye Jin

2016-09-01

This study was conducted to assess predictor variables of husbands in multicultural families and examine the relationship among variables after setting up a hypothetical model including influencing factors, so as to provide a framework necessary for developing nursing interventions of domestic violence. The participants were 260 husbands in multicultural families in four cities in Korea. Data were analyzed using SPSS 22.0 and AMOS 20.0. Self-control, social support, family of origin violence experience and stress on cultural adaptation directly affected to dysfunctional communication, and the explanatory power of the variables was 64.7%. Family of origin violence experience in domestic stress on cultural adaptation, and dysfunctional communication were directly related to domestic violence in multicultural families, and the explanatory power of the variables was 64.6%. We found out that all variables in the model had mediation effects to domestic violence through dysfunctional communication. In other words, self-control and social support had complete mediation effects, and family of origin violence experience in domestic violence and stress on cultural adaptation had partial mediation effects. The variables explained in this study should be considered as predictive factors of domestic violence in multicultural families, and used to provide preventive nursing intervention. Our resutls can be taken into account for developing and implementing programs on alleviating dysfunctional communication in multicultural families in Korea. Copyright © 2016. Published by Elsevier B.V.

Multiple Use One-Sided Hypotheses Testing in Univariate Linear Calibration

NASA Technical Reports Server (NTRS)

Krishnamoorthy, K.; Kulkarni, Pandurang M.; Mathew, Thomas

1996-01-01

Consider a normally distributed response variable, related to an explanatory variable through the simple linear regression model. Data obtained on the response variable, corresponding to known values of the explanatory variable (i.e., calibration data), are to be used for testing hypotheses concerning unknown values of the explanatory variable. We consider the problem of testing an unlimited sequence of one sided hypotheses concerning the explanatory variable, using the corresponding sequence of values of the response variable and the same set of calibration data. This is the situation of multiple use of the calibration data. The tests derived in this context are characterized by two types of uncertainties: one uncertainty associated with the sequence of values of the response variable, and a second uncertainty associated with the calibration data. We derive tests based on a condition that incorporates both of these uncertainties. The solution has practical applications in the decision limit problem. We illustrate our results using an example dealing with the estimation of blood alcohol concentration based on breath estimates of the alcohol concentration. In the example, the problem is to test if the unknown blood alcohol concentration of an individual exceeds a threshold that is safe for driving.

Independent contrasts and PGLS regression estimators are equivalent.

PubMed

Blomberg, Simon P; Lefevre, James G; Wells, Jessie A; Waterhouse, Mary

2012-05-01

We prove that the slope parameter of the ordinary least squares regression of phylogenetically independent contrasts (PICs) conducted through the origin is identical to the slope parameter of the method of generalized least squares (GLSs) regression under a Brownian motion model of evolution. This equivalence has several implications: 1. Understanding the structure of the linear model for GLS regression provides insight into when and why phylogeny is important in comparative studies. 2. The limitations of the PIC regression analysis are the same as the limitations of the GLS model. In particular, phylogenetic covariance applies only to the response variable in the regression and the explanatory variable should be regarded as fixed. Calculation of PICs for explanatory variables should be treated as a mathematical idiosyncrasy of the PIC regression algorithm. 3. Since the GLS estimator is the best linear unbiased estimator (BLUE), the slope parameter estimated using PICs is also BLUE. 4. If the slope is estimated using different branch lengths for the explanatory and response variables in the PIC algorithm, the estimator is no longer the BLUE, so this is not recommended. Finally, we discuss whether or not and how to accommodate phylogenetic covariance in regression analyses, particularly in relation to the problem of phylogenetic uncertainty. This discussion is from both frequentist and Bayesian perspectives.

Spatial analysis of trace elements in a moss bio-monitoring data over France by accounting for source, protocol and environmental parameters.

PubMed

Lequy, Emeline; Saby, Nicolas P A; Ilyin, Ilia; Bourin, Aude; Sauvage, Stéphane; Leblond, Sébastien

2017-07-15

Air pollution in trace elements (TE) remains a concern for public health in Europe. For this reasons, networks of air pollution concentrations or exposure are deployed, including a moss bio-monitoring programme in Europe. Spatial determinants of TE concentrations in mosses remain unclear. In this study, the French dataset of TE in mosses is analyzed by spatial autoregressive model to account for spatial structure of the data and several variables proven or suspected to affect TE concentrations in mosses. Such variables include source (atmospheric deposition and soil concentrations), protocol (sampling month, collector, and moss species), and environment (forest type and canopy density, distance to the coast or the highway, and elevation). Modeled atmospheric deposition was only available for Cd and Pb and was one of the main explanatory variables of the concentrations in mosses. Predicted soil content was also an important explanatory variable except for Cr, Ni, and Zn. However, the moss species was the main factor for all the studied TE. The other environmental variables affected differently the TE. In particular, the forest type and canopy density were important in most cases. These results stress the need for further research on the effect of the moss species on the capture and retention of TE, as well as for accounting for several variables and the spatial structure of the data in statistical analyses. Copyright © 2017 Elsevier B.V. All rights reserved.

Predictive modeling of hazardous waste landfill total above-ground biomass using passive optical and LIDAR remotely sensed data

NASA Astrophysics Data System (ADS)

Hadley, Brian Christopher

This dissertation assessed remotely sensed data and geospatial modeling technique(s) to map the spatial distribution of total above-ground biomass present on the surface of the Savannah River National Laboratory's (SRNL) Mixed Waste Management Facility (MWMF) hazardous waste landfill. Ordinary least squares (OLS) regression, regression kriging, and tree-structured regression were employed to model the empirical relationship between in-situ measured Bahia (Paspalum notatum Flugge) and Centipede [Eremochloa ophiuroides (Munro) Hack.] grass biomass against an assortment of explanatory variables extracted from fine spatial resolution passive optical and LIDAR remotely sensed data. Explanatory variables included: (1) discrete channels of visible, near-infrared (NIR), and short-wave infrared (SWIR) reflectance, (2) spectral vegetation indices (SVI), (3) spectral mixture analysis (SMA) modeled fractions, (4) narrow-band derivative-based vegetation indices, and (5) LIDAR derived topographic variables (i.e. elevation, slope, and aspect). Results showed that a linear combination of the first- (1DZ_DGVI), second- (2DZ_DGVI), and third-derivative of green vegetation indices (3DZ_DGVI) calculated from hyperspectral data recorded over the 400--960 nm wavelengths of the electromagnetic spectrum explained the largest percentage of statistical variation (R2 = 0.5184) in the total above-ground biomass measurements. In general, the topographic variables did not correlate well with the MWMF biomass data, accounting for less than five percent of the statistical variation. It was concluded that tree-structured regression represented the optimum geospatial modeling technique due to a combination of model performance and efficiency/flexibility factors.

An Economic Model of U.S. Airline Operating Expenses

NASA Technical Reports Server (NTRS)

Harris, Franklin D.

2005-01-01

This report presents a new economic model of operating expenses for 67 airlines. The model is based on data that the airlines reported to the United States Department of Transportation in 1999. The model incorporates expense-estimating equations that capture direct and indirect expenses of both passenger and cargo airlines. The variables and business factors included in the equations are detailed enough to calculate expenses at the flight equipment reporting level. Total operating expenses for a given airline are then obtained by summation over all aircraft operated by the airline. The model's accuracy is demonstrated by correlation with the DOT Form 41 data from which it was derived. Passenger airlines are more accurately modeled than cargo airlines. An appendix presents a concise summary of the expense estimating equations with explanatory notes. The equations include many operational and aircraft variables, which accommodate any changes that airline and aircraft manufacturers might make to lower expenses in the future. In 1999, total operating expenses of the 67 airlines included in this study amounted to slightly over $100.5 billion. The economic model reported herein estimates $109.3 billion.

A cross-national analysis of how economic inequality predicts biodiversity loss.

PubMed

Holland, Tim G; Peterson, Garry D; Gonzalez, Andrew

2009-10-01

We used socioeconomic models that included economic inequality to predict biodiversity loss, measured as the proportion of threatened plant and vertebrate species, across 50 countries. Our main goal was to evaluate whether economic inequality, measured as the Gini index of income distribution, improved the explanatory power of our statistical models. We compared four models that included the following: only population density, economic footprint (i.e., the size of the economy relative to the country area), economic footprint and income inequality (Gini index), and an index of environmental governance. We also tested the environmental Kuznets curve hypothesis, but it was not supported by the data. Statistical comparisons of the models revealed that the model including both economic footprint and inequality was the best predictor of threatened species. It significantly outperformed population density alone and the environmental governance model according to the Akaike information criterion. Inequality was a significant predictor of biodiversity loss and significantly improved the fit of our models. These results confirm that socioeconomic inequality is an important factor to consider when predicting rates of anthropogenic biodiversity loss.

Multilevel Modeling with Correlated Effects

ERIC Educational Resources Information Center

Kim, Jee-Seon; Frees, Edward W.

2007-01-01

When there exist omitted effects, measurement error, and/or simultaneity in multilevel models, explanatory variables may be correlated with random components, and standard estimation methods do not provide consistent estimates of model parameters. This paper introduces estimators that are consistent under such conditions. By employing generalized…

Understanding burnout according to individual differences: ongoing explanatory power evaluation of two models for measuring burnout types

PubMed Central

2012-01-01

Background The classic determination of burnout is by means of the dimensions exhaustion, cynicism and inefficacy. A new definition of the syndrome is based on clinical subtypes, consisting of “frenetic” (involved, ambitious, overloaded), “underchallenged” (indifferent, bored, with lack of personal development) and “worn-out” (neglectful, unacknowledged, with little control). The dimensions of overload, lack of development and neglect form a shortened version of this perspective. The aims of this study were to estimate and to compare the explanatory power of both typological models, short and long, with the standard measurement. Methods This was a cross-sectional survey with a randomly sample of university employees (n=409). Multivariate linear regression models were constructed between the “Maslach Burnout Inventory General Survey” (MBI-GS) dimensions, as dependent variables, and the “Burnout Clinical Subtype Questionnaire” (BCSQ-36 and BCSQ-12) dimensions, as independent variables. Results The BCSQ-36 subscales together explained 53% of ‘exhaustion’ (p<0.001), 59% of ‘cynicism’ (p<0.001) and 37% of ‘efficacy’ (p<0.001), while BCSQ-12 subscales explained 44% of ‘exhaustion’ (p<0.001), 44% of ‘cynicism’ (p<0.001), and 30% of ‘efficacy’ (p<0.001). The difference in the explanatory power of both models was significant for ‘exhaustion’ (p<0.001), and for ‘cynicism’ (p<0.001) and ‘efficacy (p<0.001). Conclusions Both BCSQ-36 and BCSQ-12 demonstrate great explanatory power over the standard MBI-GS, while offering a useful characterization of the syndrome for the evaluation and design of interventions tailored to the characteristics of each individual. The BCSQ-36 may be very useful in mental health services, given that it provides a good deal of information, while the BCSQ-12 could be used as a screening measure in primary care consultations owing to its simplicity and functional nature. PMID:23110723

Beliefs about causes, symptoms, and stigma associated with severe mental illness among 'highly acculturated' Chinese-American patients.

PubMed

Lin, Susan Y

2013-12-01

Literature about experiences of mental illness among ethnic minority has tended to focus on first-generation migrants. This study fills that gap by exploring experiences among highly acculturated Chinese-American patients with mental illness. Twenty-nine participants completed semi-structured interviews based on Kleinman's explanatory model, which were audio-taped, transcribed and coded for qualitative analysis. Beliefs about the causes of mental illness included biological factors, head trauma and personal losses. Issues relating to stigma and shame were also discussed. Highly acculturated ethnic minority patients may ascribe to a biomedical model at the same time as ascribing to culture-specific beliefs.

Examining school effectiveness at the fourth grade: A hierarchical analysis of the Third International Mathematics and Science Study (TIMSS)

NASA Astrophysics Data System (ADS)

Stemler, Steven Edward

This study explored school effectiveness in mathematics and science at the fourth grade using data from IEA's Third International Mathematics and Science Study (TIMSS). Fourteen of the 26 countries participating in TIMSS at the fourth grade possessed sufficient between-school variability in mathematics achievement to justify the creation of explanatory models of school effectiveness while 13 countries possessed sufficient between-school variability in science achievement. Exploratory models were developed using variables drawn from student, teacher, and school questionnaires. The variables were chosen to represent the domains of student involvement, instructional methods, classroom organization, school climate, and school structure. Six explanatory models for each subject were analyzed using two-level hierarchical linear modeling (HLM) and were compared to models using only school mean SES as an explanatory variable. The amount of variability in student achievement in mathematics attributable to differences between schools ranged from 16% in Cyprus to 56% in Latvia, while the amount of between-school variance in science achievement ranged from 12% in Korea to 59% in Latvia. In general, about one-quarter of the variability in mathematics and science achievement was found to lie between schools. The research findings revealed that after adjusting for differences in student backgrounds across schools, the most effective schools in mathematics and science had students who reported seeing a positive relationship between hard work, belief in their own abilities, and achievement. In addition, more effective schools had students who reported less frequent use of computers and calculators in the classroom. These relationships were found to be stable across explanatory models, cultural contexts, and subject areas. This study has contributed a unique element to the literature by examining school effectiveness at the fourth grade across two subject areas and across 14 different countries. The results indicate that further exploration of the relationship between school effectiveness and student locus of control warrants serious consideration. Future research on school effectiveness is recommended, perhaps using trend data and looking at different grade levels.

Darwinism and cultural change.

PubMed

Godfrey-Smith, Peter

2012-08-05

Evolutionary models of cultural change have acquired an important role in attempts to explain the course of human evolution, especially our specialization in knowledge-gathering and intelligent control of environments. In both biological and cultural change, different patterns of explanation become relevant at different 'grains' of analysis and in contexts associated with different explanatory targets. Existing treatments of the evolutionary approach to culture, both positive and negative, underestimate the importance of these distinctions. Close attention to grain of analysis motivates distinctions between three possible modes of cultural evolution, each associated with different empirical assumptions and explanatory roles.

Infection Elicited Autoimmunity and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: An Explanatory Model

PubMed Central

Blomberg, Jonas; Gottfries, Carl-Gerhard; Elfaitouri, Amal; Rizwan, Muhammad; Rosén, Anders

2018-01-01

Myalgic encephalomyelitis (ME) often also called chronic fatigue syndrome (ME/CFS) is a common, debilitating, disease of unknown origin. Although a subject of controversy and a considerable scientific literature, we think that a solid understanding of ME/CFS pathogenesis is emerging. In this study, we compiled recent findings and placed them in the context of the clinical picture and natural history of the disease. A pattern emerged, giving rise to an explanatory model. ME/CFS often starts after or during an infection. A logical explanation is that the infection initiates an autoreactive process, which affects several functions, including brain and energy metabolism. According to our model for ME/CFS pathogenesis, patients with a genetic predisposition and dysbiosis experience a gradual development of B cell clones prone to autoreactivity. Under normal circumstances these B cell offsprings would have led to tolerance. Subsequent exogenous microbial exposition (triggering) can lead to comorbidities such as fibromyalgia, thyroid disorder, and orthostatic hypotension. A decisive infectious trigger may then lead to immunization against autoantigens involved in aerobic energy production and/or hormone receptors and ion channel proteins, producing postexertional malaise and ME/CFS, affecting both muscle and brain. In principle, cloning and sequencing of immunoglobulin variable domains could reveal the evolution of pathogenic clones. Although evidence consistent with the model accumulated in recent years, there are several missing links in it. Hopefully, the hypothesis generates testable propositions that can augment the understanding of the pathogenesis of ME/CFS. PMID:29497420

MODELING TREE LEVEL PROCESSES

EPA Science Inventory

An overview of three main types of simulation approach (explanatory, abstraction, and estimation) is presented, along with a discussion of their capabilities limitations, and the steps required for their validation. A process model being developed through the Forest Response Prog...

Induction-related cost of patients with acute myeloid leukaemia in France.

PubMed

Nerich, Virginie; Lioure, Bruno; Rave, Maryline; Recher, Christian; Pigneux, Arnaud; Witz, Brigitte; Escoffre-Barbe, Martine; Moles, Marie-Pierre; Jourdan, Eric; Cahn, Jean Yves; Woronoff-Lemsi, Marie-Christine

2011-04-01

The economic profile of acute myeloid leukaemia (AML) is badly known. The few studies published on this disease are now relatively old and include small numbers of patients. The purpose of this retrospective study was to evaluate the induction-related cost of 500 patients included in the AML 2001 trial, and to determine the explanatory factors of cost. "Induction" patient's hospital stay from admission for "induction" to discharge after induction. The study was performed from the French Public Health insurance perspective, restrictive to hospital institution costs. The average management of a hospital stay for "induction" was evaluated according to the analytical accounting of Besançon University Teaching Hospital and the French public Diagnosis-Related Group database. Multiple linear regression was used to search for explanatory factors. Only direct medical costs were included: treatment and hospitalisation. Mean induction-related direct medical cost was estimated at €41,852 ± 6,037, with a mean length of hospital stay estimated at 36.2 ± 10.7 days. After adjustment for age, sex and performance status, only two explanatory factors were found: an additional induction course and salvage course increased induction-related cost by 38% (± 4) and 15% (± 1) respectively, in comparison to one induction. These explanatory factors were associated with a significant increase in the mean length of hospital stay: 45.8 ± 11.6 days for 2 inductions and 38.5 ± 15.5 if the patient had a salvage course, in comparison to 32.9 ± 7.7 for one induction (P < 10⁻⁴). This result is robust and was confirmed by sensitivity analysis. Consideration of economic constraints in health care is now a reality. Only the control of length of hospital stay may lead to a decrease in induction-related cost for patients with AML.

Logit Models for the Analysis of Two-Way Categorical Data

ERIC Educational Resources Information Center

Draxler, Clemens

2011-01-01

This article discusses the application of logit models for the analyses of 2-way categorical observations. The models described are generalized linear models using the logit link function. One of the models is the Rasch model (Rasch, 1960). The objective is to test hypotheses of marginal and conditional independence between explanatory quantities…

The evolutionary interplay of intergroup conflict and altruism in humans: a review of parochial altruism theory and prospects for its extension.

PubMed

Rusch, Hannes

2014-11-07

Drawing on an idea proposed by Darwin, it has recently been hypothesized that violent intergroup conflict might have played a substantial role in the evolution of human cooperativeness and altruism. The central notion of this argument, dubbed 'parochial altruism', is that the two genetic or cultural traits, aggressiveness against the out-groups and cooperativeness towards the in-group, including self-sacrificial altruistic behaviour, might have coevolved in humans. This review assesses the explanatory power of current theories of 'parochial altruism'. After a brief synopsis of the existing literature, two pitfalls in the interpretation of the most widely used models are discussed: potential direct benefits and high relatedness between group members implicitly induced by assumptions about conflict structure and frequency. Then, a number of simplifying assumptions made in the construction of these models are pointed out which currently limit their explanatory power. Next, relevant empirical evidence from several disciplines which could guide future theoretical extensions is reviewed. Finally, selected alternative accounts of evolutionary links between intergroup conflict and intragroup cooperation are briefly discussed which could be integrated with parochial altruism in the future. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

The role of ability, motivation, and opportunity to work in the transition from work to early retirement--testing and optimizing the Early Retirement Model.

PubMed

de Wind, Astrid; Geuskens, Goedele A; Ybema, Jan Fekke; Bongers, Paulien M; van der Beek, Allard J

2015-01-01

Determinants in the domains health, job characteristics, skills, and social and financial factors may influence early retirement through three central explanatory variables, namely, the ability, motivation, and opportunity to work. Based on the literature, we created the Early Retirement Model. This study aims to investigate whether data support the model and how it could be improved. Employees aged 58-62 years (N=1862), who participated in the first three waves of the Dutch Study on Transitions in Employment, Ability and Motivation (STREAM) were included. Determinants were assessed at baseline, central explanatory variables after one year, and early retirement after two years. Structural equation modeling was applied. Testing the Early Retirement Model resulted in a model with good fit. Health, job characteristics, skills, and social and financial factors were related to the ability, motivation and/or opportunity to work (significant β range: 0.05-0.31). Lower work ability (β=-0.13) and less opportunity to work (attitude colleagues and supervisor about working until age 65: β=-0.24) predicted early retirement, whereas the motivation to work (work engagement) did not. The model could be improved by adding direct effects of three determinants on early retirement, ie, support of colleagues and supervisor (β=0.14), positive attitude of the partner with respect to early retirement (β=0.15), and not having a partner (β=-0.13). The Early Retirement Model was largely supported by the data but could be improved. The prolongation of working life might be promoted by work-related interventions focusing on health, work ability, the social work climate, social norms on prolonged careers, and the learning environment.

Understanding and Forecasting Ethnolinguistic Vitality

ERIC Educational Resources Information Center

Karan, Mark E.

2011-01-01

Forecasting of ethnolinguistic vitality can only be done within a well-functioning descriptive and explanatory model of the dynamics of language stability and shift. It is proposed that the Perceived Benefit Model of Language Shift, used with a taxonomy of language shift motivations, provides that model. The model, based on individual language…

A Note on the Heterogeneous Choice Model

ERIC Educational Resources Information Center

Rohwer, Goetz

2015-01-01

The heterogeneous choice model (HCM) has been proposed as an extension of the standard logit and probit models, which allows taking into account different error variances of explanatory variables. In this note, I show that in an important special case, this model is just another way to specify an interaction effect.

The Relationship between Students' Epistemologies and Model-Based Reasoning.

ERIC Educational Resources Information Center

Gobert, Janice; Discenna, Jennifer

Models and modeling are frequently used as instructional tools in science education to convey important information concerning both the explanatory and structural features of topic areas in science. The efficacy of models as such rests almost entirely upon students' ability to conceptualize them as abstracted "representations" of…

Targets, Effects, and Perpetrators of Sexual Harassment in Newsrooms.

ERIC Educational Resources Information Center

Brown, Cindy M.; Flatow, Gail M.

1997-01-01

Surveys Indiana journalists, finding that two models tested (the sociocultural model and the organizational model, both grounded in conception of power differences between harassed and harasser) have explanatory power, but that they explain the same results in different ways and sometimes combinations of the models provide better explanations of…

Predictive Modeling of a Fecal Indicator at a Subtropical Marine Beach

EPA Science Inventory

The Virtual Beach Model Builder (VBMB) is a software tool that can be used to develop predictive models at beaches based on microbial data and observations (explanatory variables) that describe hydrometeorological and biogeochemical conditions. During the summer of 2008, a study...

Landscape risk factors for Lyme disease in the eastern broadleaf forest province of the Hudson River valley and the effect of explanatory data classification resolution.

PubMed

Messier, Kyle P; Jackson, Laura E; White, Jennifer L; Hilborn, Elizabeth D

2015-01-01

This study assessed how landcover classification affects associations between landscape characteristics and Lyme disease rate. Landscape variables were derived from the National Land Cover Database (NLCD), including native classes (e.g., deciduous forest, developed low intensity) and aggregate classes (e.g., forest, developed). Percent of each landcover type, median income, and centroid coordinates were calculated by census tract. Regression results from individual and aggregate variable models were compared with the dispersion parameter-based R(2) (Rα(2)) and AIC. The maximum Rα(2) was 0.82 and 0.83 for the best aggregate and individual model, respectively. The AICs for the best models differed by less than 0.5%. The aggregate model variables included forest, developed, agriculture, agriculture-squared, y-coordinate, y-coordinate-squared, income and income-squared. The individual model variables included deciduous forest, deciduous forest-squared, developed low intensity, pasture, y-coordinate, y-coordinate-squared, income, and income-squared. Results indicate that regional landscape models for Lyme disease rate are robust to NLCD landcover classification resolution. Published by Elsevier Ltd.

Spatial modelling of landscape aesthetic potential in urban-rural fringes.

PubMed

Sahraoui, Yohan; Clauzel, Céline; Foltête, Jean-Christophe

2016-10-01

The aesthetic potential of landscape has to be modelled to provide tools for land-use planning. This involves identifying landscape attributes and revealing individuals' landscape preferences. Landscape aesthetic judgments of individuals (n = 1420) were studied by means of a photo-based survey. A set of landscape visibility metrics was created to measure landscape composition and configuration in each photograph using spatial data. These metrics were used as explanatory variables in multiple linear regressions to explain aesthetic judgments. We demonstrate that landscape aesthetic judgments may be synthesized in three consensus groups. The statistical results obtained show that landscape visibility metrics have good explanatory power. Ultimately, we propose a spatial modelling of landscape aesthetic potential based on these results combined with systematic computation of visibility metrics. Copyright © 2016 Elsevier Ltd. All rights reserved.

An Explanatory Model of Self-Service on the Internet

NASA Astrophysics Data System (ADS)

Oliver, Dave; Livermore, Celia Romm; Farag, Neveen Awad

This chapter describes research that identifies and classifies the dimensions of self-service activity enabled through the Internet. Self-service is effected by organizations providing ways and means whereby customers perform tasks related to the procurement of goods and services. We describe how an instrument used to measure Internet-based self-service was developed, validated and applied. The results from applying the instrument to a large number of Web sites, covering a range of industries, countries and cultures, are analyzed and discussed. The study presents a model in which type of industry, level of technological development, income and cultural factors are proposed as explanatory variables for Web-based self-service. We conclude with an assessment of this program of research’s achievements so far.

Extended Mixed-Efects Item Response Models with the MH-RM Algorithm

ERIC Educational Resources Information Center

Chalmers, R. Philip

2015-01-01

A mixed-effects item response theory (IRT) model is presented as a logical extension of the generalized linear mixed-effects modeling approach to formulating explanatory IRT models. Fixed and random coefficients in the extended model are estimated using a Metropolis-Hastings Robbins-Monro (MH-RM) stochastic imputation algorithm to accommodate for…

Parent Predictors of Adolescents' Explanatory Style

ERIC Educational Resources Information Center

Vélez, Clorinda E.; Krause, Elizabeth D.; Brunwasser, Steven M.; Freres, Derek R.; Abenavoli, Rachel M.; Gillham, Jane E.

2015-01-01

The current study tested the prospective relations (6-month lag) between three aspects of the parent-child relationship at Time 1 (T1) and adolescents' explanatory styles at Time 2 (T2): caregiving behaviors, parents' explanatory style for their own negative events, and parents' explanatory style for their children's negative events. The sample…

Towards a computational(ist) neurobiology of language: Correlational, integrated, and explanatory neurolinguistics*

PubMed Central

Poeppel, David

2014-01-01

We outline what an integrated approach to language research that connects experimental, theoretical, and neurobiological domains of inquiry would look like, and ask to what extent unification is possible across domains. At the center of the program is the idea that computational/representational (CR) theories of language must be used to investigate its neurobiological (NB) foundations. We consider different ways in which CR and NB might be connected. These are (1) A Correlational way, in which NB computation is correlated with the CR theory; (2) An Integrated way, in which NB data provide crucial evidence for choosing among CR theories; and (3) an Explanatory way, in which properties of NB explain why a CR theory is the way it is. We examine various questions concerning the prospects for Explanatory connections in particular, including to what extent it makes sense to say that NB could be specialized for particular computations. PMID:25914888

Towards a computational(ist) neurobiology of language: Correlational, integrated, and explanatory neurolinguistics.

PubMed

Embick, David; Poeppel, David

2015-05-01

We outline what an integrated approach to language research that connects experimental, theoretical, and neurobiological domains of inquiry would look like, and ask to what extent unification is possible across domains. At the center of the program is the idea that computational/representational (CR) theories of language must be used to investigate its neurobiological (NB) foundations. We consider different ways in which CR and NB might be connected. These are (1) A Correlational way, in which NB computation is correlated with the CR theory; (2) An Integrated way, in which NB data provide crucial evidence for choosing among CR theories; and (3) an Explanatory way, in which properties of NB explain why a CR theory is the way it is. We examine various questions concerning the prospects for Explanatory connections in particular, including to what extent it makes sense to say that NB could be specialized for particular computations.

A journey of a thousand miles begins with one small step - human agency, hydrological processes and time in socio-hydrology

NASA Astrophysics Data System (ADS)

Ertsen, M. W.; Murphy, J. T.; Purdue, L. E.; Zhu, T.

2014-04-01

When simulating social action in modeling efforts, as in socio-hydrology, an issue of obvious importance is how to ensure that social action by human agents is well-represented in the analysis and the model. Generally, human decision-making is either modeled on a yearly basis or lumped together as collective social structures. Both responses are problematic, as human decision-making is more complex and organizations are the result of human agency and cannot be used as explanatory forces. A way out of the dilemma of how to include human agency is to go to the largest societal and environmental clustering possible: society itself and climate, with time steps of years or decades. In the paper, another way out is developed: to face human agency squarely, and direct the modeling approach to the agency of individuals and couple this with the lowest appropriate hydrological level and time step. This approach is supported theoretically by the work of Bruno Latour, the French sociologist and philosopher. We discuss irrigation archaeology, as it is in this discipline that the issues of scale and explanatory force are well discussed. The issue is not just what scale to use: it is what scale matters. We argue that understanding the arrangements that permitted the management of irrigation over centuries requires modeling and understanding the small-scale, day-to-day operations and personal interactions upon which they were built. This effort, however, must be informed by the longer-term dynamics, as these provide the context within which human agency is acted out.

A journey of a thousand miles begins with one small step - human agency, hydrological processes and time in socio-hydrology

NASA Astrophysics Data System (ADS)

Ertsen, M. W.; Murphy, J. T.; Purdue, L. E.; Zhu, T.

2013-11-01

When simulating social action in modeling efforts, as in socio-hydrology, an issue of obvious importance is how to ensure that social action by human agents is well-represented in the analysis and the model. Generally, human decision-making is either modeled on a yearly basis or lumped together as collective social structures. Both responses are problematic, as human decision making is more complex and organizations are the result of human agency and cannot be used as explanatory forces. A way out of the dilemma how to include human agency is to go to the largest societal and environmental clustering possible: society itself and climate, with time steps of years or decades. In the paper, the other way out is developed: to face human agency squarely, and direct the modeling approach to the human agency of individuals and couple this with the lowest appropriate hydrological level and time step. This approach is supported theoretically by the work of Bruno Latour, the French sociologist and philosopher. We discuss irrigation archaeology, as it is in this discipline that the issues of scale and explanatory force are well discussed. The issue is not just what scale to use: it is what scale matters. We argue that understanding the arrangements that permitted the management of irrigation over centuries, requires modeling and understanding the small-scale, day-to-day operations and personal interactions upon which they were built. This effort, however, must be informed by the longer-term dynamics as these provide the context within which human agency, is acted out.

Climate Change Impacts on Migration in the Vulnerable Countries

NASA Astrophysics Data System (ADS)

An, Nazan; Incealtin, Gamze; Kurnaz, M. Levent; Şengün Ucal, Meltem

2014-05-01

This work focuses on the economic, demographic and environmental drivers of migration related with the sustainable development in underdeveloped and developed countries, which are the most vulnerable to the climate change impacts through the Climate-Development Modeling including climate modeling and panel logit data analysis. We have studied some countries namely Bangladesh, Netherlands, Morocco, Malaysia, Ethiopia and Bolivia. We have analyzed these countries according to their economic, demographic and environmental indicators related with the determinants of migration, and we tried to indicate that their conditions differ according to all these factors concerning with the climate change impacts. This modeling covers some explanatory variables, which have the relationship with the migration, including GDP per capita, population, temperature and precipitation, which indicate the seasonal differences according to the years, the occurrence of natural hazards over the years, coastal location of countries, permanent cropland areas and fish capture which represents the amount of capturing over the years. We analyzed that whether there is a relationship between the migration and these explanatory variables. In order to achieve sustainable development by preventing or decreasing environmental migration due to climate change impacts or related other factors, these countries need to maintain economic, social, political, demographic, and in particular environmental performance. There are some significant risks stemming from climate change, which is not under control. When the economic and environmental conditions are considered, we have to regard climate change to be the more destructive force for those who are less defensible against all of these risks and impacts of uncontrolled climate change. This work was supported by the BU Research Fund under the project number 6990. One of the authors (MLK) was partially supported by Mercator-IPC Fellowship Program.

Logistic regression modeling to assess groundwater vulnerability to contamination in Hawaii, USA

NASA Astrophysics Data System (ADS)

Mair, Alan; El-Kadi, Aly I.

2013-10-01

Capture zone analysis combined with a subjective susceptibility index is currently used in Hawaii to assess vulnerability to contamination of drinking water sources derived from groundwater. In this study, we developed an alternative objective approach that combines well capture zones with multiple-variable logistic regression (LR) modeling and applied it to the highly-utilized Pearl Harbor and Honolulu aquifers on the island of Oahu, Hawaii. Input for the LR models utilized explanatory variables based on hydrogeology, land use, and well geometry/location. A suite of 11 target contaminants detected in the region, including elevated nitrate (> 1 mg/L), four chlorinated solvents, four agricultural fumigants, and two pesticides, was used to develop the models. We then tested the ability of the new approach to accurately separate groups of wells with low and high vulnerability, and the suitability of nitrate as an indicator of other types of contamination. Our results produced contaminant-specific LR models that accurately identified groups of wells with the lowest/highest reported detections and the lowest/highest nitrate concentrations. Current and former agricultural land uses were identified as significant explanatory variables for eight of the 11 target contaminants, while elevated nitrate was a significant variable for five contaminants. The utility of the combined approach is contingent on the availability of hydrologic and chemical monitoring data for calibrating groundwater and LR models. Application of the approach using a reference site with sufficient data could help identify key variables in areas with similar hydrogeology and land use but limited data. In addition, elevated nitrate may also be a suitable indicator of groundwater contamination in areas with limited data. The objective LR modeling approach developed in this study is flexible enough to address a wide range of contaminants and represents a suitable addition to the current subjective approach.

Explanatory style across the life span: evidence for stability over 52 years.

PubMed

Burns, M O; Seligman, M E

1989-03-01

Analyzed explanatory style across the life span. 30 Ss whose average age was 72 responded to questions about their current life and provided diaries or letters written in their youth, an average of 52 years earlier. A blind content analysis of explanatory style derived from these 2 sources revealed that explanatory style for negative events was stable throughout adult life (r = .54, p less than .002). In contrast, there appeared to be no stability of explanatory style for positive events between the same 2 time periods. These results suggest that explanatory style for negative events may persist across the life span and may constitute an enduring risk factor for depression, low achievement, and physical illness.

Modeling sheep pox disease from the 1994-1998 epidemic in Evros Prefecture, Greece.

PubMed

Malesios, C; Demiris, N; Abas, Z; Dadousis, K; Koutroumanidis, T

2014-10-01

Sheep pox is a highly transmissible disease which can cause serious loss of livestock and can therefore have major economic impact. We present data from sheep pox epidemics which occurred between 1994 and 1998. The data include weekly records of infected farms as well as a number of covariates. We implement Bayesian stochastic regression models which, in addition to various explanatory variables like seasonal and environmental/meteorological factors, also contain serial correlation structure based on variants of the Ornstein-Uhlenbeck process. We take a predictive view in model selection by utilizing deviance-based measures. The results indicate that seasonality and the number of infected farms are important predictors for sheep pox incidence. Copyright © 2014 Elsevier Ltd. All rights reserved.

Decision tree analysis of factors influencing rainfall-related building damage

NASA Astrophysics Data System (ADS)

Spekkers, M. H.; Kok, M.; Clemens, F. H. L. R.; ten Veldhuis, J. A. E.

2014-04-01

Flood damage prediction models are essential building blocks in flood risk assessments. Little research has been dedicated so far to damage of small-scale urban floods caused by heavy rainfall, while there is a need for reliable damage models for this flood type among insurers and water authorities. The aim of this paper is to investigate a wide range of damage-influencing factors and their relationships with rainfall-related damage, using decision tree analysis. For this, district-aggregated claim data from private property insurance companies in the Netherlands were analysed, for the period of 1998-2011. The databases include claims of water-related damage, for example, damages related to rainwater intrusion through roofs and pluvial flood water entering buildings at ground floor. Response variables being modelled are average claim size and claim frequency, per district per day. The set of predictors include rainfall-related variables derived from weather radar images, topographic variables from a digital terrain model, building-related variables and socioeconomic indicators of households. Analyses were made separately for property and content damage claim data. Results of decision tree analysis show that claim frequency is most strongly associated with maximum hourly rainfall intensity, followed by real estate value, ground floor area, household income, season (property data only), buildings age (property data only), ownership structure (content data only) and fraction of low-rise buildings (content data only). It was not possible to develop statistically acceptable trees for average claim size, which suggest that variability in average claim size is related to explanatory variables that cannot be defined at the district scale. Cross-validation results show that decision trees were able to predict 22-26% of variance in claim frequency, which is considerably better compared to results from global multiple regression models (11-18% of variance explained). Still, a large part of the variance in claim frequency is left unexplained, which is likely to be caused by variations in data at subdistrict scale and missing explanatory variables.

An explanatory model of community pharmacists' support in the secondary prevention of cardiovascular disease.

PubMed

Puspitasari, Hanni P; Costa, Daniel S J; Aslani, Parisa; Krass, Ines

2016-01-01

Community pharmacists have faced ongoing challenges in the delivery of clinical pharmacy services. Various attitudinal and environmental factors have been found to be associated with the provision of general clinical pharmacy services or services which focus on a specific condition, including cardiovascular disease (CVD). However, the interrelationship and relative influence of explanatory factors has not been investigated. To develop a model illustrating influences on CVD support provision by community pharmacists. Mail surveys were sent to a random sample of 1350 Australian community pharmacies to investigate determinants of CVD support provision. A theoretical model modified from the Theory of Planned Behavior (TPB) was used as a framework for the survey instrument. Structural equation modeling was used to determine how pharmacists' attitudes and environmental factors influence CVD support. A response rate of 15.8% (209/1320) was obtained. The model for CVD support provision by community pharmacists demonstrated good fit: χ(2)/df = 1.403, RMSEA = 0.047 (90% CI = 0.031-0.062), CFI = 0.962, TLI = 0.955 and WRMR = 0.838. Factors found to predict CVD support included: two attitudinal latent factors ("subjective norms of pharmacists' role in CVD support" and "pharmacists' perceived responsibilities in CVD support") and environmental factors i.e. pharmacy infrastructure (documentation and a private area), workload, location; government funded pharmacy practice programs; and pharmacists' involvement with Continuing Professional Development and attendance at CVD courses. Pharmacists' attitudes appeared to be the strongest predictor of CVD support provision. The TPB framework was useful in identifying "subjective norms" and "pharmacists' beliefs" as key constructs of community pharmacists' attitudes. Community pharmacies would be able to provide such an advanced clinical service if they strongly believed that this was an acknowledged part of their scope of practice, had adequate infrastructure and employed sufficient numbers of pharmacists with appropriate and relevant knowledge. Copyright © 2016 Elsevier Inc. All rights reserved.

Empathy and Child Neglect: A Theoretical Model

ERIC Educational Resources Information Center

De Paul, Joaquin; Guibert, Maria

2008-01-01

Objective: To present an explanatory theory-based model of child neglect. This model does not address neglectful behaviors of parents with mental retardation, alcohol or drug abuse, or severe mental health problems. In this model parental behavior aimed to satisfy a child's need is considered a helping behavior and, as a consequence, child neglect…

Development of a dynamic computational model of social cognitive theory.

PubMed

Riley, William T; Martin, Cesar A; Rivera, Daniel E; Hekler, Eric B; Adams, Marc A; Buman, Matthew P; Pavel, Misha; King, Abby C

2016-12-01

Social cognitive theory (SCT) is among the most influential theories of behavior change and has been used as the conceptual basis of health behavior interventions for smoking cessation, weight management, and other health behaviors. SCT and other behavior theories were developed primarily to explain differences between individuals, but explanatory theories of within-person behavioral variability are increasingly needed as new technologies allow for intensive longitudinal measures and interventions adapted from these inputs. These within-person explanatory theoretical applications can be modeled as dynamical systems. SCT constructs, such as reciprocal determinism, are inherently dynamical in nature, but SCT has not been modeled as a dynamical system. This paper describes the development of a dynamical system model of SCT using fluid analogies and control systems principles drawn from engineering. Simulations of this model were performed to assess if the model performed as predicted based on theory and empirical studies of SCT. This initial model generates precise and testable quantitative predictions for future intensive longitudinal research. Dynamic modeling approaches provide a rigorous method for advancing health behavior theory development and refinement and for guiding the development of more potent and efficient interventions.

Measuring change for a multidimensional test using a generalized explanatory longitudinal item response model.

PubMed

Cho, Sun-Joo; Athay, Michele; Preacher, Kristopher J

2013-05-01

Even though many educational and psychological tests are known to be multidimensional, little research has been done to address how to measure individual differences in change within an item response theory framework. In this paper, we suggest a generalized explanatory longitudinal item response model to measure individual differences in change. New longitudinal models for multidimensional tests and existing models for unidimensional tests are presented within this framework and implemented with software developed for generalized linear models. In addition to the measurement of change, the longitudinal models we present can also be used to explain individual differences in change scores for person groups (e.g., learning disabled students versus non-learning disabled students) and to model differences in item difficulties across item groups (e.g., number operation, measurement, and representation item groups in a mathematics test). An empirical example illustrates the use of the various models for measuring individual differences in change when there are person groups and multiple skill domains which lead to multidimensionality at a time point. © 2012 The British Psychological Society.

Poisson Regression Analysis of Illness and Injury Surveillance Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frome E.L., Watkins J.P., Ellis E.D.

2012-12-12

The Department of Energy (DOE) uses illness and injury surveillance to monitor morbidity and assess the overall health of the work force. Data collected from each participating site include health events and a roster file with demographic information. The source data files are maintained in a relational data base, and are used to obtain stratified tables of health event counts and person time at risk that serve as the starting point for Poisson regression analysis. The explanatory variables that define these tables are age, gender, occupational group, and time. Typical response variables of interest are the number of absences duemore » to illness or injury, i.e., the response variable is a count. Poisson regression methods are used to describe the effect of the explanatory variables on the health event rates using a log-linear main effects model. Results of fitting the main effects model are summarized in a tabular and graphical form and interpretation of model parameters is provided. An analysis of deviance table is used to evaluate the importance of each of the explanatory variables on the event rate of interest and to determine if interaction terms should be considered in the analysis. Although Poisson regression methods are widely used in the analysis of count data, there are situations in which over-dispersion occurs. This could be due to lack-of-fit of the regression model, extra-Poisson variation, or both. A score test statistic and regression diagnostics are used to identify over-dispersion. A quasi-likelihood method of moments procedure is used to evaluate and adjust for extra-Poisson variation when necessary. Two examples are presented using respiratory disease absence rates at two DOE sites to illustrate the methods and interpretation of the results. In the first example the Poisson main effects model is adequate. In the second example the score test indicates considerable over-dispersion and a more detailed analysis attributes the over-dispersion to extra-Poisson variation. The R open source software environment for statistical computing and graphics is used for analysis. Additional details about R and the data that were used in this report are provided in an Appendix. Information on how to obtain R and utility functions that can be used to duplicate results in this report are provided.« less

[Multilevel analysis of the technical efficiency of hospitals in the Spanish National Health System by property and type of management].

PubMed

Pérez-Romero, Carmen; Ortega-Díaz, M Isabel; Ocaña-Riola, Ricardo; Martín-Martín, José Jesús

2018-05-11

To analyze technical efficiency by type of property and management of general hospitals in the Spanish National Health System (2010-2012) and identify hospital and regional explanatory variables. 230 hospitals were analyzed combining data envelopment analysis and fixed effects multilevel linear models. Data envelopment analysis measured overall, technical and scale efficiency, and the analysis of explanatory factors was performed using multilevel models. The average rate of overall technical efficiency of hospitals without legal personality is lower than hospitals with legal personality (0.691 and 0.876 in 2012). There is a significant variability in efficiency under variable returns (TE) by direct, indirect and mixed forms of management. The 29% of the variability in TE es attributable to the Region. Legal personality increased the TE of the hospitals by 11.14 points. On the other hand, most of the forms of management (different to those of the traditional hospitals) increased TE in varying percentages. At regional level, according to the model considered, insularity and average annual income per household are explanatory variables of TE. Having legal personality favours technical efficiency. The regulatory and management framework of hospitals, more than public or private ownership, seem to explain technical efficiency. Regional characteristics explain the variability in TE. Copyright © 2018 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Oral health of 65-year olds in Sweden and Norway: a global question and ICF, the latest conceptual model from WHO.

PubMed

Ekbäck, Gunnar; Åstrøm, Anne Nordrehaug; Klock, Kristin; Ordell, Sven; Unell, Lennart

2012-07-01

The aims of this study were to identify explanatory factors of satisfaction with oral health among Norwegian and Swedish 65 year olds in terms of items from four different domains of ICF and to compare the strengths of the various ICF domains in explaining satisfaction with oral health. Further it was to assess whether the explanatory factors of ICF domains vary between Norway and Sweden. In 2007, standardized questionnaires were mailed to all the residents in certain counties of Sweden and Norway who were born in 1942. Response rates were 73.1% (n = 6078) in Sweden and 56.0% (n = 4062) in Norway. In total, 33 questions based on four different ICF domains were chosen to explain satisfaction with oral health. Logistic regression showed that four different ICF domains in terms of body function, body structure, activity/participation and environmental factors explained, respectively, 53%, 31%, 12% and 34% of the explanatory variance in the satisfaction with oral health. In the final analysis, only nine items were statistically significant (p < 0.05). This study indicates that ICF as a conceptual model could cover a broad spectrum of factors embedded in OHRQoL measured by a global question in Sweden and Norway. Nine items, representing four ICF domains, were important in the final model for explaining satisfaction with oral health.

The use of cognitive ability measures as explanatory variables in regression analysis.

PubMed

Junker, Brian; Schofield, Lynne Steuerle; Taylor, Lowell J

2012-12-01

Cognitive ability measures are often taken as explanatory variables in regression analysis, e.g., as a factor affecting a market outcome such as an individual's wage, or a decision such as an individual's education acquisition. Cognitive ability is a latent construct; its true value is unobserved. Nonetheless, researchers often assume that a test score , constructed via standard psychometric practice from individuals' responses to test items, can be safely used in regression analysis. We examine problems that can arise, and suggest that an alternative approach, a "mixed effects structural equations" (MESE) model, may be more appropriate in many circumstances.

Does IQ explain socio-economic differentials in total and cardiovascular disease mortality? Comparison with the explanatory power of traditional cardiovascular disease risk factors in the Vietnam Experience Study.

PubMed

Batty, G David; Shipley, Martin J; Dundas, Ruth; Macintyre, Sally; Der, Geoff; Mortensen, Laust H; Deary, Ian J

2009-08-01

The aim of this study was to examine the explanatory power of intelligence (IQ) compared with traditional cardiovascular disease (CVD) risk factors in the relationship of socio-economic disadvantage with total and CVD mortality, that is the extent to which IQ may account for the variance in this well-documented association. Cohort study of 4289 US male former military personnel with data on four widely used markers of socio-economic position (early adulthood and current income, occupational prestige, and education), IQ test scores (early adulthood and middle-age), a range of nine established CVD risk factors (systolic and diastolic blood pressure, total blood cholesterol, HDL cholesterol, body mass index, smoking, blood glucose, resting heart rate, and forced expiratory volume in 1 s), and later mortality. We used the relative index of inequality (RII) to quantify the relation between each index of socio-economic position and mortality. Fifteen years of mortality surveillance gave rise to 237 deaths (62 from CVD and 175 from 'other' causes). In age-adjusted analyses, as expected, each of the four indices of socio-economic position was inversely associated with total, CVD, and 'other' causes of mortality, such that elevated rates were evident in the most socio-economically disadvantaged men. When IQ in middle-age was introduced to the age-adjusted model, there was marked attenuation in the RII across the socio-economic predictors for total mortality (average 50% attenuation in RII), CVD (55%), and 'other' causes of death (49%). When the nine traditional risk factors were added to the age-adjusted model, the comparable reduction in RII was less marked than that seen after IQ adjustment: all-causes (40%), CVD (40%), and 'other' mortality (43%). Adding IQ to the latter model resulted in marked, additional explanatory power for all outcomes in comparison to the age-adjusted analyses: all-causes (63%), CVD (63%), and 'other' mortality (65%). When we utilized IQ in early adulthood rather than middle-age as an explanatory variable, the attenuating effect on the socio-economic gradient was less pronounced although the same pattern was still present. In the present analyses of socio-economic gradients in total and CVD mortality, IQ appeared to offer greater explanatory power than that apparent for traditional CVD risk factors.

An explanatory model for state Medicaid per capita prescription drug expenditures.

PubMed

Roy, Sanjoy; Madhavan, S Suresh

2012-01-01

Rising prescription drug expenditure is a growing concern for publicly funded drug benefit programs like Medicaid. To be able to contain drug expenditures in Medicaid, it is important that cause(s) for such increases are identified. This study attempts to establish an explanatory model for Medicaid prescription drugs expenditure based on the impacts of key influencers/predictors identified using a comprehensive framework of drug utilization. A modified Andersen's behavior model of health services utilization is employed to identify potential determinants of pharmaceutical expenditures in state Medicaid programs. Level of federal matching funds, access to primary care, severity of diseases, unemployment, and education levels were found to be key influencers of Medicaid prescription drug expenditure. Increases in all, except education levels, were found to result in increases in drug expenditures. Findings from this study could better inform intervention policies and cost-containment strategies for state Medicaid drug benefit programs.

A Philosophical Perspective on Evolutionary Systems Biology

PubMed Central

Soyer, Orkun S.; Siegal, Mark L.

2015-01-01

Evolutionary systems biology (ESB) is an emerging hybrid approach that integrates methods, models, and data from evolutionary and systems biology. Drawing on themes that arose at a cross-disciplinary meeting on ESB in 2013, we discuss in detail some of the explanatory friction that arises in the interaction between evolutionary and systems biology. These tensions appear because of different modeling approaches, diverse explanatory aims and strategies, and divergent views about the scope of the evolutionary synthesis. We locate these discussions in the context of long-running philosophical deliberations on explanation, modeling, and theoretical synthesis. We show how many of the issues central to ESB’s progress can be understood as general philosophical problems. The benefits of addressing these philosophical issues feed back into philosophy too, because ESB provides excellent examples of scientific practice for the development of philosophy of science and philosophy of biology. PMID:26085823

Use of regression‐based models to map sensitivity of aquatic resources to atmospheric deposition in Yosemite National Park, USA

USGS Publications Warehouse

Clow, David W.; Nanus, Leora; Huggett, Brian

2010-01-01

An abundance of exposed bedrock, sparse soil and vegetation, and fast hydrologic flushing rates make aquatic ecosystems in Yosemite National Park susceptible to nutrient enrichment and episodic acidification due to atmospheric deposition of nitrogen (N) and sulfur (S). In this study, multiple linear regression (MLR) models were created to estimate fall‐season nitrate and acid neutralizing capacity (ANC) in surface water in Yosemite wilderness. Input data included estimated winter N deposition, fall‐season surface‐water chemistry measurements at 52 sites, and basin characteristics derived from geographic information system layers of topography, geology, and vegetation. The MLR models accounted for 84% and 70% of the variance in surface‐water nitrate and ANC, respectively. Explanatory variables (and the sign of their coefficients) for nitrate included elevation (positive) and the abundance of neoglacial and talus deposits (positive), unvegetated terrain (positive), alluvium (negative), and riparian (negative) areas in the basins. Explanatory variables for ANC included basin area (positive) and the abundance of metamorphic rocks (positive), unvegetated terrain (negative), water (negative), and winter N deposition (negative) in the basins. The MLR equations were applied to 1407 stream reaches delineated in the National Hydrography Data Set for Yosemite, and maps of predicted surface‐water nitrate and ANC concentrations were created. Predicted surface‐water nitrate concentrations were highest in small, high‐elevation cirques, and concentrations declined downstream. Predicted ANC concentrations showed the opposite pattern, except in high‐elevation areas underlain by metamorphic rocks along the Sierran Crest, which had relatively high predicted ANC (>200 μeq L−1). Maps were created to show where basin characteristics predispose aquatic resources to nutrient enrichment and acidification effects from N and S deposition. The maps can be used to help guide development of water‐quality programs designed to monitor and protect natural resources in national parks.

Uni- and multi-variable modelling of flood losses: experiences gained from the Secchia river inundation event.

NASA Astrophysics Data System (ADS)

Carisi, Francesca; Domeneghetti, Alessio; Kreibich, Heidi; Schröter, Kai; Castellarin, Attilio

2017-04-01

Flood risk is function of flood hazard and vulnerability, therefore its accurate assessment depends on a reliable quantification of both factors. The scientific literature proposes a number of objective and reliable methods for assessing flood hazard, yet it highlights a limited understanding of the fundamental damage processes. Loss modelling is associated with large uncertainty which is, among other factors, due to a lack of standard procedures; for instance, flood losses are often estimated based on damage models derived in completely different contexts (i.e. different countries or geographical regions) without checking its applicability, or by considering only one explanatory variable (i.e. typically water depth). We consider the Secchia river flood event of January 2014, when a sudden levee-breach caused the inundation of nearly 200 km2 in Northern Italy. In the aftermath of this event, local authorities collected flood loss data, together with additional information on affected private households and industrial activities (e.g. buildings surface and economic value, number of company's employees and others). Based on these data we implemented and compared a quadratic-regression damage function, with water depth as the only explanatory variable, and a multi-variable model that combines multiple regression trees and considers several explanatory variables (i.e. bagging decision trees). Our results show the importance of data collection revealing that (1) a simple quadratic regression damage function based on empirical data from the study area can be significantly more accurate than literature damage-models derived for a different context and (2) multi-variable modelling may outperform the uni-variable approach, yet it is more difficult to develop and apply due to a much higher demand of detailed data.

Anthropogenic Habitats Facilitate Dispersal of an Early Successional Obligate: Implications for Restoration of an Endangered Ecosystem.

PubMed

Amaral, Katrina E; Palace, Michael; O'Brien, Kathleen M; Fenderson, Lindsey E; Kovach, Adrienne I

2016-01-01

Landscape modification and habitat fragmentation disrupt the connectivity of natural landscapes, with major consequences for biodiversity. Species that require patchily distributed habitats, such as those that specialize on early successional ecosystems, must disperse through a landscape matrix with unsuitable habitat types. We evaluated landscape effects on dispersal of an early successional obligate, the New England cottontail (Sylvilagus transitionalis). Using a landscape genetics approach, we identified barriers and facilitators of gene flow and connectivity corridors for a population of cottontails in the northeastern United States. We modeled dispersal in relation to landscape structure and composition and tested hypotheses about the influence of habitat fragmentation on gene flow. Anthropogenic and natural shrubland habitats facilitated gene flow, while the remainder of the matrix, particularly development and forest, impeded gene flow. The relative influence of matrix habitats differed between study areas in relation to a fragmentation gradient. Barrier features had higher explanatory power in the more fragmented site, while facilitating features were important in the less fragmented site. Landscape models that included a simultaneous barrier and facilitating effect of roads had higher explanatory power than models that considered either effect separately, supporting the hypothesis that roads act as both barriers and facilitators at all spatial scales. The inclusion of LiDAR-identified shrubland habitat improved the fit of our facilitator models. Corridor analyses using circuit and least cost path approaches revealed the importance of anthropogenic, linear features for restoring connectivity between the study areas. In fragmented landscapes, human-modified habitats may enhance functional connectivity by providing suitable dispersal conduits for early successional specialists.

Anthropogenic Habitats Facilitate Dispersal of an Early Successional Obligate: Implications for Restoration of an Endangered Ecosystem

PubMed Central

Amaral, Katrina E.; Palace, Michael; O’Brien, Kathleen M.; Fenderson, Lindsey E.; Kovach, Adrienne I.

2016-01-01

Landscape modification and habitat fragmentation disrupt the connectivity of natural landscapes, with major consequences for biodiversity. Species that require patchily distributed habitats, such as those that specialize on early successional ecosystems, must disperse through a landscape matrix with unsuitable habitat types. We evaluated landscape effects on dispersal of an early successional obligate, the New England cottontail (Sylvilagus transitionalis). Using a landscape genetics approach, we identified barriers and facilitators of gene flow and connectivity corridors for a population of cottontails in the northeastern United States. We modeled dispersal in relation to landscape structure and composition and tested hypotheses about the influence of habitat fragmentation on gene flow. Anthropogenic and natural shrubland habitats facilitated gene flow, while the remainder of the matrix, particularly development and forest, impeded gene flow. The relative influence of matrix habitats differed between study areas in relation to a fragmentation gradient. Barrier features had higher explanatory power in the more fragmented site, while facilitating features were important in the less fragmented site. Landscape models that included a simultaneous barrier and facilitating effect of roads had higher explanatory power than models that considered either effect separately, supporting the hypothesis that roads act as both barriers and facilitators at all spatial scales. The inclusion of LiDAR-identified shrubland habitat improved the fit of our facilitator models. Corridor analyses using circuit and least cost path approaches revealed the importance of anthropogenic, linear features for restoring connectivity between the study areas. In fragmented landscapes, human-modified habitats may enhance functional connectivity by providing suitable dispersal conduits for early successional specialists. PMID:26954014

Bayesian spatio-temporal modeling of particulate matter concentrations in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Manga, Edna; Awang, Norhashidah

2016-06-01

This article presents an application of a Bayesian spatio-temporal Gaussian process (GP) model on particulate matter concentrations from Peninsular Malaysia. We analyze daily PM10 concentration levels from 35 monitoring sites in June and July 2011. The spatiotemporal model set in a Bayesian hierarchical framework allows for inclusion of informative covariates, meteorological variables and spatiotemporal interactions. Posterior density estimates of the model parameters are obtained by Markov chain Monte Carlo methods. Preliminary data analysis indicate information on PM10 levels at sites classified as industrial locations could explain part of the space time variations. We include the site-type indicator in our modeling efforts. Results of the parameter estimates for the fitted GP model show significant spatio-temporal structure and positive effect of the location-type explanatory variable. We also compute some validation criteria for the out of sample sites that show the adequacy of the model for predicting PM10 at unmonitored sites.

Adaptive non-interventional heuristics for covariation detection in causal induction: model comparison and rational analysis.

PubMed

Hattori, Masasi; Oaksford, Mike

2007-09-10

In this article, 41 models of covariation detection from 2 × 2 contingency tables were evaluated against past data in the literature and against data from new experiments. A new model was also included based on a limiting case of the normative phi-coefficient under an extreme rarity assumption, which has been shown to be an important factor in covariation detection (McKenzie & Mikkelsen, 2007) and data selection (Hattori, 2002; Oaksford & Chater, 1994, 2003). The results were supportive of the new model. To investigate its explanatory adequacy, a rational analysis using two computer simulations was conducted. These simulations revealed the environmental conditions and the memory restrictions under which the new model best approximates the normative model of covariation detection in these tasks. They thus demonstrated the adaptive rationality of the new model. 2007 Cognitive Science Society, Inc.

Optical Properties of Three Beach Waters: Implications for Predictive Modeling of Enterococci

EPA Science Inventory

Sunlight plays an important role in the inactivation of fecal indicator bacteria in recreational waters. Solar radiation can explain temporal trends in bacterial counts and is commonly used as an explanatory variable in predictive models. Broadband surface radiation provides a ba...

Determinants of urban sprawl in European cities

PubMed Central

Alvanides, Seraphim; Garrod, Guy

2015-01-01

This paper provides empirical evidence that helps to answer several key questions relating to the extent of urban sprawl in Europe. Building on the monocentric city model, this study uses existing data sources to derive a set of panel data for 282 European cities at three time points (1990, 2000 and 2006). Two indices of urban sprawl are calculated that, respectively, reflect changes in artificial area and the levels of urban fragmentation for each city. These are supplemented by a set of data on various economic and geographical variables that might explain the variation of the two indices. Using a Hausman-Taylor estimator and random regressors to control for the possible correlation between explanatory variables and unobservable city-level effects, we find that the fundamental conclusions of the standard monocentric model are valid in the European context for both indices. Although the variables generated by the monocentric model explain a large part of the variation of artificial area, their explanatory power for modelling the fragmentation index is relatively low. PMID:26321770

Determinants of urban sprawl in European cities.

PubMed

Oueslati, Walid; Alvanides, Seraphim; Garrod, Guy

2015-07-01

This paper provides empirical evidence that helps to answer several key questions relating to the extent of urban sprawl in Europe. Building on the monocentric city model, this study uses existing data sources to derive a set of panel data for 282 European cities at three time points (1990, 2000 and 2006). Two indices of urban sprawl are calculated that, respectively, reflect changes in artificial area and the levels of urban fragmentation for each city. These are supplemented by a set of data on various economic and geographical variables that might explain the variation of the two indices. Using a Hausman-Taylor estimator and random regressors to control for the possible correlation between explanatory variables and unobservable city-level effects, we find that the fundamental conclusions of the standard monocentric model are valid in the European context for both indices. Although the variables generated by the monocentric model explain a large part of the variation of artificial area, their explanatory power for modelling the fragmentation index is relatively low.

Introduction to Multilevel Item Response Theory Analysis: Descriptive and Explanatory Models

ERIC Educational Resources Information Center

Sulis, Isabella; Toland, Michael D.

2017-01-01

Item response theory (IRT) models are the main psychometric approach for the development, evaluation, and refinement of multi-item instruments and scaling of latent traits, whereas multilevel models are the primary statistical method when considering the dependence between person responses when primary units (e.g., students) are nested within…

An Explanatory Model of Teacher Movement within Ontario School Boards

ERIC Educational Resources Information Center

Sibbald, Timothy M.

2017-01-01

Teacher movement within school boards is examined using multiple case study. Emergent themes achieved theoretical saturation and are consistent with the research literature. In this paper, the relationships between the themes are used to develop a substantive theoretical model of teacher movement within school boards. The model uses a two-phase…

Cost Efficiency in the University: A Departmental Evaluation Model

ERIC Educational Resources Information Center

Gimenez, Victor M.; Martinez, Jose Luis

2006-01-01

This article presents a model for the analysis of cost efficiency within the framework of data envelopment analysis models. It calculates the cost excess, separating a unit of production from its optimal or frontier levels, and, at the same time, breaks these excesses down into three explanatory factors: (a) technical inefficiency, which depends…

Identifying Multiple Levels of Discussion-Based Teaching Strategies for Constructing Scientific Models

ERIC Educational Resources Information Center

Williams, Grant; Clement, John

2015-01-01

This study sought to identify specific types of discussion-based strategies that two successful high school physics teachers using a model-based approach utilized in attempting to foster students' construction of explanatory models for scientific concepts. We found evidence that, in addition to previously documented dialogical strategies that…

Family Interaction Patterns Associated with Self-Esteem in Preadolescent Girls and Boys.

ERIC Educational Resources Information Center

Loeb, Roger C.; And Others

This study used behavioral measures of family interaction to examine four traditional explanatory models for the influence of parents on their children's self-esteem. The four models examined were: (1) identification/modeling, (2) directiveness, (3) reinforcement, and (4) warmth/involvement. A total of 98 fourth- and fifth-grade girls and boys…

Color doppler in clinical cardiology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duncan, W.J.

1987-01-01

A presentation of color doppler, which enables physicians to pinpoint problems and develop effective treatment. State-of-the-art illustrations and layout, with color images and explanatory text are included.

Linking Adverse Childhood Effects and Attachment: A Theory of Etiology for Sexual Offending.

PubMed

Grady, Melissa D; Levenson, Jill S; Bolder, Tess

2016-01-25

Sexual violence continues to be a significant public health problem affecting significant portions of the population. Unfortunately, an agreed upon theory of etiology remains elusive leading to challenges in developing effective prevention and treatment interventions. Recently, there is a growing body of literature examining the role of adverse childhood experiences (ACEs) in the development of sexually violent behavior. This research has begun to explore the rates of various types of child maltreatments and family dysfunction in individuals who have been convicted of a sexual crime. These empirical inquiries have been primarily descriptive in nature and have not yet provided a cohesive theoretical model as to why the presence of ACEs might contribute to sexually abusive behavior. This article suggests that attachment theory offers an explanatory link between early adversity and sexually abusive behavior in adulthood. We first summarize important attachment theory concepts, then integrate them with research in the area of developmental psychopathology and ACEs, and finally propose a model by which attachment can be used as an explanatory theory for subsequent sexualized coping and sexually abusive behaviors. Finally, this article explores the implications for practice, policy, and research using this explanatory theory as a framework for understanding sexual violence. © The Author(s) 2016.

Monitoring and modeling to predict Escherichia coli at Presque Isle Beach 2, City of Erie, Erie County, Pennsylvania

USGS Publications Warehouse

Zimmerman, Tammy M.

2006-01-01

The Lake Erie shoreline in Pennsylvania spans nearly 40 miles and is a valuable recreational resource for Erie County. Nearly 7 miles of the Lake Erie shoreline lies within Presque Isle State Park in Erie, Pa. Concentrations of Escherichia coli (E. coli) bacteria at permitted Presque Isle beaches occasionally exceed the single-sample bathing-water standard, resulting in unsafe swimming conditions and closure of the beaches. E. coli concentrations and other water-quality and environmental data collected at Presque Isle Beach 2 during the 2004 and 2005 recreational seasons were used to develop models using tobit regression analyses to predict E. coli concentrations. All variables statistically related to E. coli concentrations were included in the initial regression analyses, and after several iterations, only those explanatory variables that made the models significantly better at predicting E. coli concentrations were included in the final models. Regression models were developed using data from 2004, 2005, and the combined 2-year dataset. Variables in the 2004 model and the combined 2004-2005 model were log10 turbidity, rain weight, wave height (calculated), and wind direction. Variables in the 2005 model were log10 turbidity and wind direction. Explanatory variables not included in the final models were water temperature, streamflow, wind speed, and current speed; model results indicated these variables did not meet significance criteria at the 95-percent confidence level (probabilities were greater than 0.05). The predicted E. coli concentrations produced by the models were used to develop probabilities that concentrations would exceed the single-sample bathing-water standard for E. coli of 235 colonies per 100 milliliters. Analysis of the exceedence probabilities helped determine a threshold probability for each model, chosen such that the correct number of exceedences and nonexceedences was maximized and the number of false positives and false negatives was minimized. Future samples with computed exceedence probabilities higher than the selected threshold probability, as determined by the model, will likely exceed the E. coli standard and a beach advisory or closing may need to be issued; computed exceedence probabilities lower than the threshold probability will likely indicate the standard will not be exceeded. Additional data collected each year can be used to test and possibly improve the model. This study will aid beach managers in more rapidly determining when waters are not safe for recreational use and, subsequently, when to issue beach advisories or closings.

The consciousness state space (CSS)—a unifying model for consciousness and self

PubMed Central

Berkovich-Ohana, Aviva; Glicksohn, Joseph

2014-01-01

Every experience, those we are aware of and those we are not, is embedded in a subjective timeline, is tinged with emotion, and inevitably evokes a certain sense of self. Here, we present a phenomenological model for consciousness and selfhood which relates time, awareness, and emotion within one framework. The consciousness state space (CSS) model is a theoretical one. It relies on a broad range of literature, hence has high explanatory and integrative strength, and helps in visualizing the relationship between different aspects of experience. Briefly, it is suggested that all phenomenological states fall into two categories of consciousness, core and extended (CC and EC, respectively). CC supports minimal selfhood that is short of temporal extension, its scope being the here and now. EC supports narrative selfhood, which involves personal identity and continuity across time, as well as memory, imagination and conceptual thought. The CSS is a phenomenological space, created by three dimensions: time, awareness and emotion. Each of the three dimensions is shown to have a dual phenomenological composition, falling within CC and EC. The neural spaces supporting each of these dimensions, as well as CC and EC, are laid out based on the neuroscientific literature. The CSS dynamics include two simultaneous trajectories, one in CC and one in EC, typically antagonistic in normal experiences. However, this characteristic behavior is altered in states in which a person experiences an altered sense of self. Two examples are laid out, flow and meditation. The CSS model creates a broad theoretical framework with explanatory and unificatory power. It constructs a detailed map of the consciousness and selfhood phenomenology, which offers constraints for the science of consciousness. We conclude by outlining several testable predictions raised by the CSS model. PMID:24808870

Explanatory variables for adult patients' self-reported recovery after acute lateral ankle sprain.

PubMed

van Rijn, Rogier M; Willemsen, Sten P; Verhagen, Arianne P; Koes, Bart W; Bierma-Zeinstra, Sita M A

2011-01-01

Longitudinal research on musculoskeletal disorders often makes use of a single measure of recovery, despite the large variation in reported recovery that exists. Patients with an acute ankle sprain often experience no pain or functional disability following treatment, yet report not being fully recovered, or vice versa. The purpose of this study was to find explanatory variables for reporting recovery by analyzing the extent to which different outcomes (eg, pain intensity) were associated with recovery and how baseline scores of different variables influence this association in adult patients after acute lateral ankle sprain. This was a cohort study based on data collected in a randomized controlled trial (RCT). This study was constructed within the framework of an RCT. One hundred two patients who incurred an acute ankle sprain were included. Recovery, pain intensity, giving way of the ankle, and Ankle Function Score (AFS) were assessed during the RCT at baseline and at 4 weeks, 8 weeks, 3 months, and 12 months postinjury. Mean differences were calculated between baseline and follow-up. Associations were calculated using linear mixed models, and the influence of baseline scores on these associations was determined using linear regression with interaction. Associations were found between recovery and the mean differences of pain during running on flat and rough surfaces (4 and 8 weeks, 3 months) and between recovery and the mean difference of giving way of the ankle during walking on a rough surface (8 weeks, 3 months). This study used data collected from an RCT. Therefore, the study was limited to the outcomes measured in that trial, and some explanatory factors easily could have been missed. This study is the first to identify explanatory variables for reporting recovery in adults after ankle sprain. Pain intensity and giving way of the ankle measured during high ankle load activities make it easier to measure and to generalize recovery in this population and should be the primary outcome measures of interest. This study indicates the huge need to reach consensus about primary outcome measures for research in patients sustaining ankle sprains.

Narrative insight in psychosis: The relationship with spiritual and religious explanatory frameworks.

PubMed

Marriott, Michael R; Thompson, Andrew R; Cockshutt, Graham; Rowse, Georgina

2018-03-25

When considering psychosis, the concept of narrative insight has been offered as an alternative to clinical insight in determining individuals' responses to their difficulties, as it allows for a more holistic and person-centred framework to be embraced within professional practice. This study aims to explore the validity of the narrative insight construct within a group of people who have experienced psychosis. Inductive qualitative methods were used to explore how eight participants utilized spiritual or religious explanatory frameworks for their experiences of psychosis and to consider these in relation to the construct of narrative insight. Semi-structured interviews were undertaken with individuals who identified themselves as interested in spiritual or religious ideas and whose self-reported experiences which were identified as akin to psychosis by experienced academic clinicians. Transcriptions from these interviews were subject to interpretative phenomenological analysis within a broader research question; a selection of themes and data from the resultant phenomenological structure are explored here for their relevance to narrative insight. Participants discussed spiritual and biological explanations for their experiences and were able to hold alternative potential explanations alongside each other. They were reflective regarding the origins of their explanations and would describe a process of testing and proof in relation to them. These findings suggest that the narrative insight construct has the potential to be a valid approach to understanding experiences of psychosis, and challenge the dominance of the clinical insight construct within clinical practice. Clinicians should value the explanatory framework for experiences which are provided by individuals experiencing psychosis, and encourage them to develop a framework which is coherent to their own world view rather than predominantly pursuing a biomedical explanation. Assessments of psychosis should be adapted to include an understanding of the cohesiveness of the individual's explanatory framework and personal value to them, with a reduced focus on their acceptance of biomedical models of 'illness'. Care and care research for individuals experiencing psychosis should consider the value of narrative insight within future developments. © 2018 The Authors. Psychology and Psychotherapy: Theory, Research and Practice published by John Wiley & Sons Ltd on behalf of British Psychological Society.

Year-class formation of upper St. Lawrence River northern pike

USGS Publications Warehouse

Smith, B.M.; Farrell, J.M.; Underwood, H.B.; Smith, S.J.

2007-01-01

Variables associated with year-class formation in upper St. Lawrence River northern pike Esox lucius were examined to explore population trends. A partial least-squares (PLS) regression model (PLS 1) was used to relate a year-class strength index (YCSI; 1974-1997) to explanatory variables associated with spawning and nursery areas (seasonal water level and temperature and their variability, number of ice days, and last day of ice presence). A second model (PLS 2) incorporated four additional ecological variables: potential predators (abundance of double-crested cormorants Phalacrocorax auritus and yellow perch Perca flavescens), female northern pike biomass (as a measure of stock-recruitment effects), and total phosphorus (productivity). Trends in adult northern pike catch revealed a decline (1981-2005), and year-class strength was positively related to catch per unit effort (CPUE; R2 = 0.58). The YCSI exceeded the 23-year mean in only 2 of the last 10 years. Cyclic patterns in the YCSI time series (along with strong year-classes every 4-6 years) were apparent, as was a dampening effect of amplitude beginning around 1990. The PLS 1 model explained over 50% of variation in both explanatory variables and the dependent variable, YCSI first-order moving-average residuals. Variables retained (N = 10; Wold's statistic ??? 0.8) included negative YCSI associations with high summer water levels, high variability in spring and fall water levels, and variability in fall water temperature. The YCSI exhibited positive associations with high spring, summer, and fall water temperature, variability in spring temperature, and high winter and spring water level. The PLS 2 model led to positive YCSI associations with phosphorus and yellow perch CPUE and a negative correlation with double-crested cormorant abundance. Environmental variables (water level and temperature) are hypothesized to regulate northern pike YCSI cycles, and dampening in YCSI magnitude may be related to a combination of factors, including wetland habitat changes, reduced nutrient loading, and increased predation by double-crested cormorants. ?? Copyright by the American Fisheries Society 2007.

Explanatory Versus Pragmatic Trials: An Essential Concept in Study Design and Interpretation.

PubMed

Merali, Zamir; Wilson, Jefferson R

2017-11-01

Randomized clinical trials often represent the highest level of clinical evidence available to evaluate the efficacy of an intervention in clinical medicine. Although the process of randomization serves to maximize internal validity, the external validity, or generalizability, of such studies depends on several factors determined at the design phase of the trial including eligibility criteria, study setting, and outcomes of interest. In general, explanatory trials are optimized to demonstrate the efficacy of an intervention in a highly selected patient group; however, findings from these studies may not be generalizable to the larger clinical problem. In contrast, pragmatic trials attempt to understand the real-world benefit of an intervention by incorporating design elements that allow for greater generalizability and clinical applicability of study results. In this article we describe the explanatory-pragmatic continuum for clinical trials in greater detail. Further, a well-accepted tool for grading trials on this continuum is described, and applied, to 2 recently published trials pertaining to the surgical management of lumbar degenerative spondylolisthesis.

Modification of the Integrated Sasang Constitutional Diagnostic Model

PubMed Central

Nam, Jiho

2017-01-01

In 2012, the Korea Institute of Oriental Medicine proposed an objective and comprehensive physical diagnostic model to address quantification problems in the existing Sasang constitutional diagnostic method. However, certain issues have been raised regarding a revision of the proposed diagnostic model. In this paper, we propose various methodological approaches to address the problems of the previous diagnostic model. Firstly, more useful variables are selected in each component. Secondly, the least absolute shrinkage and selection operator is used to reduce multicollinearity without the modification of explanatory variables. Thirdly, proportions of SC types and age are considered to construct individual diagnostic models and classify the training set and the test set for reflecting the characteristics of the entire dataset. Finally, an integrated model is constructed with explanatory variables of individual diagnosis models. The proposed integrated diagnostic model significantly improves the sensitivities for both the male SY type (36.4% → 62.0%) and the female SE type (43.7% → 64.5%), which were areas of limitation of the previous integrated diagnostic model. The ideas of these new algorithms are expected to contribute not only to the scientific development of Sasang constitutional medicine in Korea but also to that of other diagnostic methods for traditional medicine. PMID:29317897

The use of cognitive ability measures as explanatory variables in regression analysis

PubMed Central

Junker, Brian; Schofield, Lynne Steuerle; Taylor, Lowell J

2015-01-01

Cognitive ability measures are often taken as explanatory variables in regression analysis, e.g., as a factor affecting a market outcome such as an individual’s wage, or a decision such as an individual’s education acquisition. Cognitive ability is a latent construct; its true value is unobserved. Nonetheless, researchers often assume that a test score, constructed via standard psychometric practice from individuals’ responses to test items, can be safely used in regression analysis. We examine problems that can arise, and suggest that an alternative approach, a “mixed effects structural equations” (MESE) model, may be more appropriate in many circumstances. PMID:26998417

[Treatment of functional somatic syndrome with abdominal pain].

PubMed

Abe, Tetsuya; Kanbara, Kenji; Mizuno, Yasuyuki; Fukunaga, Mikihiko

2009-09-01

Functional somatic syndrome (FSS) with abdominal pain include functional gastrointestinal disorder, chronic pancreatitis, chronic pelvic pain syndrome, which generally contain autonomic dysfunction. Regarding the treatment of FSS, it is important to know about FSS for a therapist at first. Secondly, the therapist should find out physical dysfunction of patients positively, and confirm objectively the hypotheses about both peripheral and central pathophysiological mechanisms as much as possible. Heart rate variability is an easy method, and useful to assess autonomic function. After grasping the patient's explanatory model about the illness, the therapist showes the most acceptable treatment for the patient at last.

Static and dynamic controls on fire activity at moderate spatial and temporal scales in the Alaskan boreal forest

USGS Publications Warehouse

Barrett, Kirsten; Loboda, Tatiana; McGuire, A. David; Genet, Hélène; Hoy, Elizabeth; Kasischke, Eric

2016-01-01

Wildfire, a dominant disturbance in boreal forests, is highly variable in occurrence and behavior at multiple spatiotemporal scales. New data sets provide more detailed spatial and temporal observations of active fires and the post-burn environment in Alaska. In this study, we employ some of these new data to analyze variations in fire activity by developing three explanatory models to examine the occurrence of (1) seasonal periods of elevated fire activity using the number of MODIS active fire detections data set (MCD14DL) within an 11-day moving window, (2) unburned patches within a burned area using the Monitoring Trends in Burn Severity fire severity product, and (3) short-to-moderate interval (<60 yr) fires using areas of burned area overlap in the Alaska Large Fire Database. Explanatory variables for these three models included dynamic variables that can change over the course of the fire season, such as weather and burn date, as well as static variables that remain constant over a fire season, such as topography, drainage, vegetation cover, and fire history. We found that seasonal periods of high fire activity are associated with both seasonal timing and aggregated weather conditions, as well as the landscape composition of areas that are burning. Important static inputs to the model of seasonal fire activity indicate that when fire weather conditions are suitable, areas that typically resist fire (e.g., deciduous stands) may become more vulnerable to burning and therefore less effective as fire breaks. The occurrence of short-to-moderate interval fires appears to be primarily driven by weather conditions, as these were the only relevant explanatory variables in the model. The unique importance of weather in explaining short-to-moderate interval fires implies that fire return intervals (FRIs) will be sensitive to projected climate changes in the region. Unburned patches occur most often in younger stands, which may be related to a greater deciduous fraction of vegetation as well as lower fuel loads compared with mature stands. The fraction of unburned patches may therefore increase in response to decreasing FRIs and increased deciduousness in the region, or these may decrease if fire weather conditions become more severe.

Case formulation and management using pattern-based formulation (PBF) methodology: clinical case 1.

PubMed

Fernando, Irosh; Cohen, Martin

2014-02-01

A tool for psychiatric case formulation known as pattern-based formulation (PBF) has been recently introduced. This paper presents an application of this methodology in formulating and managing complex clinical cases. The symptomatology of the clinical presentation has been parsed into individual clinical phenomena and interpreted by selecting explanatory models. The clinical presentation demonstrates how PBF has been used as a clinical tool to guide clinicians' thinking, that takes a structured approach to manage multiple issues using a broad range of management strategies. In doing so, the paper also introduces a number of patterns related to the observed clinical phenomena that can be re-used as explanatory models when formulating other clinical cases. It is expected that this paper will assist clinicians, and particularly trainees, to better understand PBF methodology and apply it to improve their formulation skills.

Insight in Psychosis: An Indicator of Severity of Psychosis, an Explanatory Model of Illness, and a Coping Strategy

PubMed Central

Jacob, K. S.

2016-01-01

Recent studies related to insight, explanatory models (EMs) of illness and their relationship to outcome of psychosis are reviewed. The traditional argument that insight predicts outcome in psychosis is not supported by recent longitudinal data, which has been analyzed using multivariable statistics that adjust for severity and quality of illness. While all cognition will have a neurobiological representation, if “insight” is related to the primary psychotic process, then insight cannot be seen as an independent predictor of outcome but a part of the progression of illness. The evidence suggests insight, like all EMs, is belief which interacts with the trajectory of the person's illness and the local culture to produce a unique understanding of the illness for the particular individual and his/her family. PMID:27335513

Explanatory model of psychosis: impact on perception of self-stigma by patients in three sub-saharan African cities.

PubMed

Makanjuola, Victor; Esan, Yomi; Oladeji, Bibilola; Kola, Lola; Appiah-Poku, John; Harris, Benjamin; Othieno, Caleb; Price, Leshawndra; Seedat, Soraya; Gureje, Oye

2016-12-01

Most cultures in sub-Saharan Africa subscribe to the belief that the root cause of psychosis is supernatural. Individuals in the community who hold a religiomagical explanatory model of causation have been shown to exhibit more stigmatizing attitudes towards people with psychosis. Self-stigma among individuals with psychosis is less frequently studied. We used a mixed-method approach, consisting of key informant's interviews to elicit information on explanatory models of causation of psychosis and questionnaire assessment of internalized stigma with an adapted version of the Scale for Internalized Stigma of Mental Illness. Twenty-four, 31, and 30 subjects with recent experience of utilizing the service of traditional or faith healers for severe mental disorders in Ibadan (Nigeria), Kumasi (Ghana), and Nairobi (Kenya), respectively, were interviewed. About 44 % (42.1 %) of the Nigerian respondents had a high (severe) level of self-stigma with the respective proportions among Ghanaian and Kenyan respondents being 20.7 and 37.5 %. Compared with 4 out of a total of 12 respondents (33.3 %) who reported low self-stigma reported supernatural attribution, 14 out of 20 respondents (70 %) with the highest level of self-stigma reported supernatural attribution across the three sites. When low scorers ascribed supernatural causation, it was often with a religious focus. There is a greater tendency for persons with high levels of self-stigma than those with low levels to ascribe supernatural attribution to their experience of a severe mental health condition.

Quantified biotic and abiotic responses to multiple stress in freshwater, marine and ground waters.

PubMed

Nõges, Peeter; Argillier, Christine; Borja, Ángel; Garmendia, Joxe Mikel; Hanganu, Jenică; Kodeš, Vit; Pletterbauer, Florian; Sagouis, Alban; Birk, Sebastian

2016-01-01

We reviewed 219 papers and built an inventory of 532 items of ecological evidence on multiple stressor impacts in rivers, lakes, transitional and coastal waters, as well as groundwaters. Our review revealed that, despite the existence of a huge conceptual knowledge base in aquatic ecology, few studies actually provide quantitative evidence on multi-stress effects. Nutrient stress was involved in 71% to 98% of multi-stress situations in the three types of surface water environments, and in 42% of those in groundwaters. However, their impact manifested differently along the groundwater-river-lake-transitional-coastal continuum, mainly determined by the different hydro-morphological features of these ecosystems. The reviewed papers addressed two-stressor combinations most frequently (42%), corresponding with the actual status-quo of pressures acting on European surface waters as reported by the Member States in the WISE WFD Database (EEA, 2015). Across all biological groups analysed, higher explanatory power of the stress-effect models was discernible for lakes under multi-stressor compared to single stressor conditions, but generally lower for coastal and transitional waters. Across all aquatic environments, the explanatory power of stress-effect models for fish increased when multi-stressor conditions were taken into account in the analysis, qualifying this organism group as a useful indicator of multi-stress effects. In contrast, the explanatory power of models using benthic flora decreased under conditions of multiple stress. Copyright © 2015 Elsevier B.V. All rights reserved.

Do nurse sows and foster litters have impaired animal welfare? Results from a cross-sectional study in sow herds.

PubMed

Sørensen, J T; Rousing, T; Kudahl, A B; Hansted, H J; Pedersen, L J

2016-04-01

Increasing litter size has led to introduction of so-called nurse sows in several EU countries. A nurse sow is a sow receiving piglets after having weaned her own piglets and thereby experiencing an extended lactation. In order to analyse whether nurse sows have more welfare problems than non-nurse sows a cross-sectional study was conducted in 57 sow herds in Denmark. Clinical observations were made on nurse and non-nurse sows and their litters. The clinical observations were dichotomized and the effect of being a nurse sow was analysed based on eight parameters: thin (body condition score<2.5), swollen bursae on legs, dew claw wounds, vulva lesions, poor hygiene, poor skin condition, shoulder lesions and cuts and wounds on the udder. Explanatory variables included in the eight models were: nurse sow (yes=1/no=0), age of piglets (weeks old, 1 to 7), parity (1 to 8+) and all first order interactions between these three variables. The effect of using nurse sows on piglet welfare was analysed with five models. The outcomes were: huddling, poor hygiene, lameness, snout cuts and carpal abrasions. The explanatory variables included in the five models were: nurse sow (yes=1/no=0), age of piglets (weeks old, 1 to 7), parity (1 to 8+) and all first order interactions between these three variables. Herd identity was included as a random factor in all models. The nurse sows had a significantly higher risk of swollen bursae on legs (P=0.038) and udder wounds (P=0.001). No differences in risk of being thin or having shoulder lesions were found. Foster litters had significantly higher risk of being dirty (P=0.026) and getting carpal abrasions (P=0.024) than non-foster litters. There was a tendency for higher lameness in foster litters than in non-foster litters (P=0.052). The results show that nurse sows and their piglets to some extent experience more welfare problems than non-nurse sows with piglets at a similar age.

Analyzing Student Learning Outcomes: Usefulness of Logistic and Cox Regression Models. IR Applications, Volume 5

ERIC Educational Resources Information Center

Chen, Chau-Kuang

2005-01-01

Logistic and Cox regression methods are practical tools used to model the relationships between certain student learning outcomes and their relevant explanatory variables. The logistic regression model fits an S-shaped curve into a binary outcome with data points of zero and one. The Cox regression model allows investigators to study the duration…

Analogical Scaffolding and the Learning of Abstract Ideas in Physics: An Example from Electromagnetic Waves

ERIC Educational Resources Information Center

Podolefsky, Noah S.; Finkelstein, Noah D.

2007-01-01

This paper describes a model of analogy, analogical scaffolding, which explains present and prior results of student learning with analogies. We build on prior models of representation, blending, and layering of ideas. Extending this model's explanatory power, we propose ways in which the model can be applied to design a curriculum directed at…

Analysis of injury severity of drivers involved in single- and two-vehicle crashes on highways in Ontario.

PubMed

Lee, Chris; Li, Xuancheng

2014-10-01

This study analyzes driver's injury severity in single- and two-vehicle crashes and compares the effects of explanatory variables among various types of crashes. The study identified factors affecting injury severity and their effects on severity levels using 5-year crash records for provincial highways in Ontario, Canada. Considering heteroscedasticity in the effects of explanatory variables on injury severity, the heteroscedastic ordered logit (HOL) models were developed for single- and two-vehicle crashes separately. The results of the models show that there exists heteroscedasticity for young drivers (≤30), safety equipment and ejection in the single-vehicle crash model, and female drivers, safety equipment and head-on collision in the two-vehicle crash models. The results also show that young car drivers have opposite effects between single-car and car-car crashes, and sideswipe crashes have opposite effects between car-car and truck-truck crashes. The study demonstrates that separate HOL models for single-vehicle and different types of two-vehicle crashes can identify differential effects of factors on driver's injury severity. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Health Belief Model as an Explanatory Framework in Communication Research: Exploring Parallel, Serial, and Moderated Mediation

PubMed Central

Jones, Christina L.; Jensen, Jakob D.; Scherr, Courtney L.; Brown, Natasha R.; Christy, Katheryn; Weaver, Jeremy

2015-01-01

The Health Belief Model (HBM) posits that messages will achieve optimal behavior change if they successfully target perceived barriers, benefits, self-efficacy, and threat. While the model seems to be an ideal explanatory framework for communication research, theoretical limitations have limited its use in the field. Notably, variable ordering is currently undefined in the HBM. Thus, it is unclear whether constructs mediate relationships comparably (parallel mediation), in sequence (serial mediation), or in tandem with a moderator (moderated mediation). To investigate variable ordering, adults (N = 1,377) completed a survey in the aftermath of an 8-month flu vaccine campaign grounded in the HBM. Exposure to the campaign was positively related to vaccination behavior. Statistical evaluation supported a model where the indirect effect of exposure on behavior through perceived barriers and threat was moderated by self-efficacy (moderated mediation). Perceived barriers and benefits also formed a serial mediation chain. The results indicate that variable ordering in the Health Belief Model may be complex, may help to explain conflicting results of the past, and may be a good focus for future research. PMID:25010519

Efficiency of dairy farms participating and not participating in veterinary herd health management programs.

PubMed

Derks, Marjolein; Hogeveen, Henk; Kooistra, Sake R; van Werven, Tine; Tauer, Loren W

2014-12-01

This paper compares farm efficiencies between dairies who were participating in a veterinary herd health management (VHHM) program with dairies not participating in such a program, to determine whether participation has an association with farm efficiency. In 2011, 572 dairy farmers received a questionnaire concerning the participation and execution of a VHHM program on their farms. Data from the questionnaire were combined with farm accountancy data from 2008 through 2012 from farms that used calendar year accounting periods, and were analyzed using Stochastic Frontier Analysis (SFA). Two separate models were specified: model 1 was the basic stochastic frontier model (output: total revenue; input: feed costs, land costs, cattle costs, non-operational costs), without explanatory variables embedded into the efficiency component of the error term. Model 2 was an expansion of model 1 which included explanatory variables (number of FTE; total kg milk delivered; price of concentrate; milk per hectare; cows per FTE; nutritional yield per hectare) inserted into the efficiency component of the joint error term. Both models were estimated with the financial parameters expressed per 100 kg fat and protein corrected milk and per cow. Land costs, cattle costs, feed costs and non-operational costs were statistically significant and positive in all models (P<0.01). Frequency distributions of the efficiency scores for the VHHM dairies and the non-VHHM dairies were plotted in a kernel density plot, and differences were tested using the Kolmogorov-Smirnov two-sample test. VHHM dairies had higher total revenue per cow, but not per 100 kg milk. For all SFA models, the difference in distribution was not statistically different between VHHM dairies and non-VHHM dairies (P values 0.94, 0.35, 0.95 and 0.89 for the basic and complete model per 100 kg fat and protein corrected milk and per cow respectively). Therefore we conclude that with our data farm participation in VHHM is not related to overall farm efficiency. Copyright © 2014 Elsevier B.V. All rights reserved.

Separating a Mixture

ERIC Educational Resources Information Center

Lotter, Christine; Taylor, Laurie

2016-01-01

In the 2 day lesson presented in this article, students explain how ionic substances interact in solutions by developing and revising their own explanatory models. The lesson engaged students in three-dimensional learning through creating and revising their own models to explain the interaction of ionic substances and polar molecules in a closed…

The Unintended Significance of Race: Environmental Racial Inequality in Detroit

ERIC Educational Resources Information Center

Downey, Liam

2005-01-01

This article addresses shortcomings in the literature on environmental inequality by (a) setting forth and testing four models of environmental inequality and (b) explicitly linking environmental inequality research to spatial mismatch theory and to the debate on the declining significance of race. The explanatory models ask whether the…

Establishing an Explanatory Model for Mathematics Identity

ERIC Educational Resources Information Center

Cribbs, Jennifer D.; Hazari, Zahra; Sonnert, Gerhard; Sadler, Philip M.

2015-01-01

This article empirically tests a previously developed theoretical framework for mathematics identity based on students' beliefs. The study employs data from more than 9,000 college calculus students across the United States to build a robust structural equation model. While it is generally thought that students' beliefs about their own competence…

Bayesian Adaptive Lasso for Ordinal Regression with Latent Variables

ERIC Educational Resources Information Center

Feng, Xiang-Nan; Wu, Hao-Tian; Song, Xin-Yuan

2017-01-01

We consider an ordinal regression model with latent variables to investigate the effects of observable and latent explanatory variables on the ordinal responses of interest. Each latent variable is characterized by correlated observed variables through a confirmatory factor analysis model. We develop a Bayesian adaptive lasso procedure to conduct…

Reliability analysis using an exponential power model with bathtub-shaped failure rate function: a Bayes study.

PubMed

Shehla, Romana; Khan, Athar Ali

2016-01-01

Models with bathtub-shaped hazard function have been widely accepted in the field of reliability and medicine and are particularly useful in reliability related decision making and cost analysis. In this paper, the exponential power model capable of assuming increasing as well as bathtub-shape, is studied. This article makes a Bayesian study of the same model and simultaneously shows how posterior simulations based on Markov chain Monte Carlo algorithms can be straightforward and routine in R. The study is carried out for complete as well as censored data, under the assumption of weakly-informative priors for the parameters. In addition to this, inference interest focuses on the posterior distribution of non-linear functions of the parameters. Also, the model has been extended to include continuous explanatory variables and R-codes are well illustrated. Two real data sets are considered for illustrative purposes.

Using Weather Data and Climate Model Output in Economic Analyses of Climate Change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Auffhammer, M.; Hsiang, S. M.; Schlenker, W.

2013-06-28

Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overviewmore » of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.« less

Developing Passenger Demand Models for International Aviation from/to Egypt: A Case Study of Cairo Airport and Egyptair

NASA Technical Reports Server (NTRS)

Abbas, Khaled A.; Fattah, Nabil Abdel; Reda, Hala R.

2003-01-01

This research is concerned with developing passenger demand models for international aviation from/to Egypt. In this context, aviation sector in Egypt is represented by the biggest and main airport namely Cairo airport as well as by the main Egyptian international air carrier namely Egyptair. The developed models utilize two variables to represent aviation demand, namely total number of international flights originating from and attracted to Cairo airport as well as total number of passengers using Egyptair international flights originating from and attracted to Cairo airport. Such demand variables were related, using different functional forms, to several explanatory variables including population, GDP and number of foreign tourists. Finally, two models were selected based on their logical acceptability, best fit and statistical significance. To demonstrate usefulness of developed models, these were used to forecast future demand patterns.

"We Decided to Call It Quits": An Exercise in Applying Duck's Dissolution Model to Students' Breakup Stories

ERIC Educational Resources Information Center

Barton, Matthew H.; Turman, Paul D.

2008-01-01

Steve Duck's scholarship has made a noticeable impact on the study of interpersonal communication. Of his works, one of the most noteworthy is the explanatory model of relationship disengagement and dissolution. Duck's Dissolution Model (DDM) explains the stages that relationships pass through when they encounter stress resulting in two…

A Reformulated Model of Barriers to Parental Involvement in Education: Comment on Hornby and Lafaele (2011)

ERIC Educational Resources Information Center

Fan, Weihua; Li, Nan; Sandoval, Jaime Robert

2018-01-01

In a 2011 article in this journal, Hornby and Lafaele provided a comprehensive model to understand barriers that may adversely impact effectiveness of parental involvement (PI) in education. The proposed explanatory model provides researchers with a new comprehensive and systematic perspective of the phenomenon in question with references from an…

Predictors of elderly mortality: health status, socioeconomic characteristics and social determinants of health.

PubMed

Mete, Cem

2005-02-01

This paper uses longitudinal survey data from Taiwan to investigate the predictors of elderly mortality. The empirical analysis confirms a relationship between socioeconomic characteristics and mortality, but this relationship weakens considerably when estimates are conditional on the health status at the time of the first wave survey. In terms of predictive power, the models with an activities of daily living index fare better (as opposed to models with self-evaluated health or self-reported illnesses). Having said that there is a payoff to the consideration of self-evaluated health jointly with other 'objective' health indicators. Other findings include a strong association between life satisfaction and survival, which prevails even after controlling for other explanatory variables. Copyright (c) 2004 John Wiley & Sons, Ltd.

Use of Symbols in Labeling. Final rule.

PubMed

2016-06-15

The Food and Drug Administration (FDA or the Agency) is issuing this final rule revising its medical device and certain biological product labeling regulations to explicitly allow for the optional inclusion of graphical representations of information, or symbols, in labeling (including labels) without adjacent explanatory text (referred to in this document as "stand-alone symbols") if certain requirements are met. The final rule also specifies that the use of symbols, accompanied by adjacent explanatory text continues to be permitted. FDA is also revising its prescription device labeling regulations to allow the use of the symbol statement "Rx only" or "[rx] only" in the labeling for prescription devices.

The effect of a negative mood priming challenge on dysfunctional attitudes, explanatory style, and explanatory flexibility.

PubMed

Fresco, David M; Heimberg, Richard G; Abramowitz, Adrienne; Bertram, Tara L

2006-06-01

Ninety-seven undergraduates, 48 of whom had a history of self-reported major depression, completed measures of mood and cognitive style (e.g. explanatory style, explanatory flexibility, dysfunctional attitudes) prior to and directly after a negative mood priming challenge that consisted of listening to sad music and thinking about an upsetting past event. Eighteen of the previously depressed participants endorsed baseline levels of depression, explanatory style for negative events, and dysfunctional attitudes higher than levels reported by never depressed participants or euthymic participants with a history of depression. All three groups (never depressed participants, dysphoric participants with a history of depression, euthymic participants with a history of depression) demonstrated increases in dysphoria and dysfunctional attitudes in response to the negative mood priming challenge. Dysphoric participants with a history of depression, but not the other two groups, evidenced modest increases in explanatory style following the negative mood priming challenge. Finally, euthymic participants with a history of depression, but not the other two groups, evidenced drops in explanatory flexibility. Findings from the present study suggest that the cognitive theories of depression may benefit from examining both cognitive content and cognitive flexibility when assessing risk for depression.

A geospatial model of ambient sound pressure levels in the contiguous United States.

PubMed

Mennitt, Daniel; Sherrill, Kirk; Fristrup, Kurt

2014-05-01

This paper presents a model that predicts measured sound pressure levels using geospatial features such as topography, climate, hydrology, and anthropogenic activity. The model utilizes random forest, a tree-based machine learning algorithm, which does not incorporate a priori knowledge of source characteristics or propagation mechanics. The response data encompasses 270 000 h of acoustical measurements from 190 sites located in National Parks across the contiguous United States. The explanatory variables were derived from national geospatial data layers and cross validation procedures were used to evaluate model performance and identify variables with predictive power. Using the model, the effects of individual explanatory variables on sound pressure level were isolated and quantified to reveal systematic trends across environmental gradients. Model performance varies by the acoustical metric of interest; the seasonal L50 can be predicted with a median absolute deviation of approximately 3 dB. The primary application for this model is to generalize point measurements to maps expressing spatial variation in ambient sound levels. An example of this mapping capability is presented for Zion National Park and Cedar Breaks National Monument in southwestern Utah.

Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks.

PubMed

Staniczenko, Phillip P A; Sivasubramaniam, Prabu; Suttle, K Blake; Pearson, Richard G

2017-06-01

Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub-disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species' presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change. © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

The role of area-level deprivation and gender in participation in population-based faecal immunochemical test (FIT) colorectal cancer screening.

PubMed

Clarke, Nicholas; McNamara, Deirdre; Kearney, Patricia M; O'Morain, Colm A; Shearer, Nikki; Sharp, Linda

2016-12-01

This study aimed to investigate the effects of sex and deprivation on participation in a population-based faecal immunochemical test (FIT) colorectal cancer screening programme. The study population included 9785 individuals invited to participate in two rounds of a population-based biennial FIT-based screening programme, in a relatively deprived area of Dublin, Ireland. Explanatory variables included in the analysis were sex, deprivation category of area of residence and age (at end of screening). The primary outcome variable modelled was participation status in both rounds combined (with "participation" defined as having taken part in either or both rounds of screening). Poisson regression with a log link and robust error variance was used to estimate relative risks (RR) for participation. As a sensitivity analysis, data were stratified by screening round. In both the univariable and multivariable models deprivation was strongly associated with participation. Increasing affluence was associated with higher participation; participation was 26% higher in people resident in the most affluent compared to the most deprived areas (multivariable RR=1.26: 95% CI 1.21-1.30). Participation was significantly lower in males (multivariable RR=0.96: 95%CI 0.95-0.97) and generally increased with increasing age (trend per age group, multivariable RR=1.02: 95%CI, 1.01-1.02). No significant interactions between the explanatory variables were found. The effects of deprivation and sex were similar by screening round. Deprivation and male gender are independently associated with lower uptake of population-based FIT colorectal cancer screening, even in a relatively deprived setting. Development of evidence-based interventions to increase uptake in these disadvantaged groups is urgently required. Copyright © 2016. Published by Elsevier Inc.

Prediction of Vigilant Attention and Cognitive Performance Using Self-Reported Alertness, Circadian Phase, Hours since Awakening, and Accumulated Sleep Loss

PubMed Central

Bermudez, Eduardo B.; Klerman, Elizabeth B.; Czeisler, Charles A.; Cohen, Daniel A.; Wyatt, James K.; Phillips, Andrew J. K.

2016-01-01

Sleep restriction causes impaired cognitive performance that can result in adverse consequences in many occupational settings. Individuals may rely on self-perceived alertness to decide if they are able to adequately perform a task. It is therefore important to determine the relationship between an individual’s self-assessed alertness and their objective performance, and how this relationship depends on circadian phase, hours since awakening, and cumulative lost hours of sleep. Healthy young adults (aged 18–34) completed an inpatient schedule that included forced desynchrony of sleep/wake and circadian rhythms with twelve 42.85-hour “days” and either a 1:2 (n = 8) or 1:3.3 (n = 9) ratio of sleep-opportunity:enforced-wakefulness. We investigated whether subjective alertness (visual analog scale), circadian phase (melatonin), hours since awakening, and cumulative sleep loss could predict objective performance on the Psychomotor Vigilance Task (PVT), an Addition/Calculation Test (ADD) and the Digit Symbol Substitution Test (DSST). Mathematical models that allowed nonlinear interactions between explanatory variables were evaluated using the Akaike Information Criterion (AIC). Subjective alertness was the single best predictor of PVT, ADD, and DSST performance. Subjective alertness alone, however, was not an accurate predictor of PVT performance. The best AIC scores for PVT and DSST were achieved when all explanatory variables were included in the model. The best AIC score for ADD was achieved with circadian phase and subjective alertness variables. We conclude that subjective alertness alone is a weak predictor of objective vigilant or cognitive performance. Predictions can, however, be improved by knowing an individual’s circadian phase, current wake duration, and cumulative sleep loss. PMID:27019198

Health system determinants of infant, child and maternal mortality: A cross-sectional study of UN member countries

PubMed Central

2011-01-01

Objective Few studies have examined the link between health system strength and important public health outcomes across nations. We examined the association between health system indicators and mortality rates. Methods We used mixed effects linear regression models to investigate the strength of association between outcome and explanatory variables, while accounting for geographic clustering of countries. We modelled infant mortality rate (IMR), child mortality rate (CMR), and maternal mortality rate (MMR) using 13 explanatory variables as outlined by the World Health Organization. Results Significant protective health system determinants related to IMR included higher physician density (adjusted rate ratio [aRR] 0.81; 95% Confidence Interval [CI] 0.71-0.91), higher sustainable access to water and sanitation (aRR 0.85; 95% CI 0.78-0.93), and having a less corrupt government (aRR 0.57; 95% CI 0.40-0.80). Out-of-pocket expenditures on health (aRR 1.29; 95% CI 1.03-1.62) were a risk factor. The same four variables were significantly related to CMR after controlling for other variables. Protective determinants of MMR included access to water and sanitation (aRR 0.88; 95% CI 0.82-0.94), having a less corrupt government (aRR 0.49; 95%; CI 0.36-0.66), and higher total expenditures on health per capita (aRR 0.84; 95% CI 0.77-0.92). Higher fertility rates (aRR 2.85; 95% CI: 2.02-4.00) were found to be a significant risk factor for MMR. Conclusion Several key measures of a health system predict mortality in infants, children, and maternal mortality rates at the national level. Improving access to water and sanitation and reducing corruption within the health sector should become priorities. PMID:22023970

Adult mental health needs and expenditure in Australia.

PubMed

Burgess, Philip; Pirkis, Jane; Buckingham, Bill; Burns, Jane; Eagar, Kathy; Eckstein, Gary

2004-06-01

Relatively little international work has examined whether mental health resource allocation matches need. This study aimed to determine whether adult mental health resources in Australia are being distributed equitably. Individual measures of need were extrapolated to Australian Areas, and Area-based proxies of need were considered. Particular attention was paid to the prevalence of mental health problems, since this is arguably the most objective measure of need. The extent to which these measures predicted public sector, private sector and total adult mental health expenditure at an Area level was examined. In the public sector, 41.6% of expenditure variation was explained by the prevalence of affective disorders, personality disorders, cognitive impairment and psychosis, as well as the Area's level of economic resources and State/Territory effects. In the private sector, 72.4% of expenditure variation was explained by service use and State/Territory effects (with an alternative model incorporating service use and State/Territory supply of private psychiatrists explaining 69.4% of expenditure variation). A relatively high proportion (58.7%) of total expenditure variation could be explained by service utilisation and State/Territory effects. For services to be delivered equitably, the majority of variation in expenditure would have to be accounted for by appropriate measures of need. The best model for public sector expenditure included an appropriate measure of need but had relatively poor explanatory power. The models for private sector and total expenditure had greater explanatory power, but relied on less appropriate measures of need. It is concluded that mental health services in Australia are not yet being delivered equitably.

Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology

USGS Publications Warehouse

Cross, Paul C.; Klaver, Robert W.; Brennan, Angela; Creel, Scott; Beckmann, Jon P.; Higgs, Megan D.; Scurlock, Brandon M.

2013-01-01

Abstract. It is increasingly common for studies of animal ecology to use model-based predictions of environmental variables as explanatory or predictor variables, even though model prediction uncertainty is typically unknown. To demonstrate the potential for misleading inferences when model predictions with error are used in place of direct measurements, we compared snow water equivalent (SWE) and snow depth as predicted by the Snow Data Assimilation System (SNODAS) to field measurements of SWE and snow depth. We examined locations on elk (Cervus canadensis) winter ranges in western Wyoming, because modeled data such as SNODAS output are often used for inferences on elk ecology. Overall, SNODAS predictions tended to overestimate field measurements, prediction uncertainty was high, and the difference between SNODAS predictions and field measurements was greater in snow shadows for both snow variables compared to non-snow shadow areas. We used a simple simulation of snow effects on the probability of an elk being killed by a predator to show that, if SNODAS prediction uncertainty was ignored, we might have mistakenly concluded that SWE was not an important factor in where elk were killed in predatory attacks during the winter. In this simulation, we were interested in the effects of snow at finer scales (2) than the resolution of SNODAS. If bias were to decrease when SNODAS predictions are averaged over coarser scales, SNODAS would be applicable to population-level ecology studies. In our study, however, averaging predictions over moderate to broad spatial scales (9–2200 km2) did not reduce the differences between SNODAS predictions and field measurements. This study highlights the need to carefully evaluate two issues when using model output as an explanatory variable in subsequent analysis: (1) the model’s resolution relative to the scale of the ecological question of interest and (2) the implications of prediction uncertainty on inferences when using model predictions as explanatory or predictor variables.

16 CFR 1101.21 - Form of notice and opportunity to comment.

Code of Federal Regulations, 2010 CFR

2010-01-01

... other relevant information the Commission intends to include with the disclosure. If the Commission... information, including a request for explanatory data or other relevant information for the Commission's... ACT REGULATIONS INFORMATION DISCLOSURE UNDER SECTION 6(b) OF THE CONSUMER PRODUCT SAFETY ACT Procedure...

Analyzing Science Teaching: A Case Study Based on Three Philosophical Models of Teaching. The Explanatory Modes Project, Background Paper No. 5.

ERIC Educational Resources Information Center

Munby, A. Hugh

The development of a category scheme for the systematic analysis of science classroom discourse is described. Three teaching models are discussed: the Impression Model, which depicts the mind of a student as receiving and storing external impressions; the Insight Model, which denies the possibility that ideas or knowledge can be conveyed by…

Classification and regression trees

Treesearch

G. G. Moisen

2008-01-01

Frequently, ecologists are interested in exploring ecological relationships, describing patterns and processes, or making spatial or temporal predictions. These purposes often can be addressed by modeling the relationship between some outcome or response and a set of features or explanatory variables.

Experimental Philosophy of Explanation Rising: The Case for a Plurality of Concepts of Explanation.

PubMed

Colombo, Matteo

2017-03-01

This paper brings together results from the philosophy and the psychology of explanation to argue that there are multiple concepts of explanation in human psychology. Specifically, it is shown that pluralism about explanation coheres with the multiplicity of models of explanation available in the philosophy of science, and it is supported by evidence from the psychology of explanatory judgment. Focusing on the case of a norm of explanatory power, the paper concludes by responding to the worry that if there is a plurality of concepts of explanation, one will not be able to normatively evaluate what counts as good explanation. Copyright © 2016 Cognitive Science Society, Inc.

Entropy-based financial asset pricing.

PubMed

Ormos, Mihály; Zibriczky, Dávid

2014-01-01

We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return-entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behavior of the beta along with entropy.

Entropy-Based Financial Asset Pricing

PubMed Central

Ormos, Mihály; Zibriczky, Dávid

2014-01-01

We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return – entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behavior of the beta along with entropy. PMID:25545668

On the nature of explanation: A PDP approach

NASA Astrophysics Data System (ADS)

Churchland, Paul M.

1990-06-01

Neural network models of sensory processing and associative memory provide the resources for a new theory of what explanatory understanding consists in. That theory finds the theoretically important factors to reside not at the level of propositions and the relations between them, but at the level of the activation patterns across large populations of neurons. The theory portrays explanatory understanding, perceptual recognition, and abductive inference as being different instances of the same more general sort of cognitive achievement, viz. prototype activation. It thus effects a unification of the theories of explanation, perception, and ampliative inference. It also finds systematic unity in the wide diversity of types of explanation (causal, functional, mathematical, intentional, reductive, etc.), a chronic problem for theories of explanation in the logico-linguistic tradition. Finally, it is free of the many defects, both logical and psychological, that plague models in that older tradition.

Obligatory Effort [Hishtadlut] as an Explanatory Model: A Critique of Reproductive Choice and Control.

PubMed

Teman, Elly; Ivry, Tsipy; Goren, Heela

2016-06-01

Studies on reproductive technologies often examine women's reproductive lives in terms of choice and control. Drawing on 48 accounts of procreative experiences of religiously devout Jewish women in Israel and the US, we examine their attitudes, understandings and experiences of pregnancy, reproductive technologies and prenatal testing. We suggest that the concept of hishtadlut-"obligatory effort"-works as an explanatory model that organizes Haredi women's reproductive careers and their negotiations of reproductive technologies. As an elastic category with negotiable and dynamic boundaries, hishtadlut gives ultra-orthodox Jewish women room for effort without the assumption of control; it allows them to exercise discretion in relation to medical issues without framing their efforts in terms of individual choice. Haredi women hold themselves responsible for making their obligatory effort and not for pregnancy outcomes. We suggest that an alternative paradigm to autonomous choice and control emerges from cosmological orders where reproductive duties constitute "obligatory choices."

The use of generalised additive models (GAM) in dentistry.

PubMed

Helfenstein, U; Steiner, M; Menghini, G

1997-12-01

Ordinary multiple regression and logistic multiple regression are widely applied statistical methods which allow a researcher to 'explain' or 'predict' a response variable from a set of explanatory variables or predictors. In these models it is usually assumed that quantitative predictors such as age enter linearly into the model. During recent years these methods have been further developed to allow more flexibility in the way explanatory variables 'act' on a response variable. The methods are called 'generalised additive models' (GAM). The rigid linear terms characterising the association between response and predictors are replaced in an optimal way by flexible curved functions of the predictors (the 'profiles'). Plotting the 'profiles' allows the researcher to visualise easily the shape by which predictors 'act' over the whole range of values. The method facilitates detection of particular shapes such as 'bumps', 'U-shapes', 'J-shapes, 'threshold values' etc. Information about the shape of the association is not revealed by traditional methods. The shapes of the profiles may be checked by performing a Monte Carlo simulation ('bootstrapping'). After the presentation of the GAM a relevant case study is presented in order to demonstrate application and use of the method. The dependence of caries in primary teeth on a set of explanatory variables is investigated. Since GAMs may not be easily accessible to dentists, this article presents them in an introductory condensed form. It was thought that a nonmathematical summary and a worked example might encourage readers to consider the methods described. GAMs may be of great value to dentists in allowing visualisation of the shape by which predictors 'act' and obtaining a better understanding of the complex relationships between predictors and response.

Neuroscience Meets Music Education: Exploring the Implications of Neural Processing Models on Music Education Practice

ERIC Educational Resources Information Center

Collins, Anita

2013-01-01

Over the past two decades, neuroscientists have been fascinated by the way the brain processes music. Using new technologies, neuroscientists offer us a better understanding of the human brain's structures and functions. They have further proposed explanatory models for how the brain processes music. While these models shed light on how the…

Teach, Coach, Live: The Viability of the Three-Role Teaching Model in the 21st Century

ERIC Educational Resources Information Center

Martin, Joseph Gregory

2016-01-01

This explanatory mixed-methods study is focused on the sustainability of the triple-threat model of teaching found at elite American boarding schools. In this model, faculty members are expected to teach, coach, and perform residential duties as part of their contract. While elite boarding schools have been researched in recent years, no research…

Pitfalls in statistical landslide susceptibility modelling

NASA Astrophysics Data System (ADS)

Schröder, Boris; Vorpahl, Peter; Märker, Michael; Elsenbeer, Helmut

2010-05-01

The use of statistical methods is a well-established approach to predict landslide occurrence probabilities and to assess landslide susceptibility. This is achieved by applying statistical methods relating historical landslide inventories to topographic indices as predictor variables. In our contribution, we compare several new and powerful methods developed in machine learning and well-established in landscape ecology and macroecology for predicting the distribution of shallow landslides in tropical mountain rainforests in southern Ecuador (among others: boosted regression trees, multivariate adaptive regression splines, maximum entropy). Although these methods are powerful, we think it is necessary to follow a basic set of guidelines to avoid some pitfalls regarding data sampling, predictor selection, and model quality assessment, especially if a comparison of different models is contemplated. We therefore suggest to apply a novel toolbox to evaluate approaches to the statistical modelling of landslide susceptibility. Additionally, we propose some methods to open the "black box" as an inherent part of machine learning methods in order to achieve further explanatory insights into preparatory factors that control landslides. Sampling of training data should be guided by hypotheses regarding processes that lead to slope failure taking into account their respective spatial scales. This approach leads to the selection of a set of candidate predictor variables considered on adequate spatial scales. This set should be checked for multicollinearity in order to facilitate model response curve interpretation. Model quality assesses how well a model is able to reproduce independent observations of its response variable. This includes criteria to evaluate different aspects of model performance, i.e. model discrimination, model calibration, and model refinement. In order to assess a possible violation of the assumption of independency in the training samples or a possible lack of explanatory information in the chosen set of predictor variables, the model residuals need to be checked for spatial auto¬correlation. Therefore, we calculate spline correlograms. In addition to this, we investigate partial dependency plots and bivariate interactions plots considering possible interactions between predictors to improve model interpretation. Aiming at presenting this toolbox for model quality assessment, we investigate the influence of strategies in the construction of training datasets for statistical models on model quality.

A Structural Equation Model Explaining 8th Grade Students' Mathematics Achievements

ERIC Educational Resources Information Center

Yurt, Eyüp; Sünbül, Ali Murat

2014-01-01

The purpose of this study is to investigate, via a model, the explanatory and predictive relationships among the following variables: Mathematical Problem Solving and Reasoning Skills, Sources of Mathematics Self-Efficacy, Spatial Ability, and Mathematics Achievements of Secondary School 8th Grade Students. The sample group of the study, itself…

Violence Prevention in United States Society of Jesus Secondary Schools

ERIC Educational Resources Information Center

Simonds, Thomas Andrew

2009-01-01

Using data from a representative number of Society of Jesus secondary schools, the researcher reports what these schools are doing to prevent violence, and tests an explanatory model of school violence he created. The researcher proposes that this model can be used to explain and prevent school violence by identifying and addressing the…

Assessing Students' Deep Conceptual Understanding in Physical Sciences: An Example on Sinking and Floating

ERIC Educational Resources Information Center

Shen, Ji; Liu, Ou Lydia; Chang, Hsin-Yi

2017-01-01

This paper presents a transformative modeling framework that guides the development of assessment to measure students' deep understanding in physical sciences. The framework emphasizes 3 types of connections that students need to make when learning physical sciences: (1) linking physical states, processes, and explanatory models, (2) integrating…

University Students' Explanatory Models of the Interactions between Electric Charges and Magnetic Fields

ERIC Educational Resources Information Center

Saglam, Murat

2010-01-01

This study aimed to investigate the models that co-existed in students' cognitive structure to explain the interactions between electric charges and uniform magnetic fields. The sample consisted of 129 first-year civil engineering, geology and geophysics students from a large state university in western Turkey. The students answered five…

Making the Transition: An Explanatory Model of Special Education Students' Participation in Postsecondary Education.

ERIC Educational Resources Information Center

Butler-Nalin, Paul; And Others

The report of the National Longitudinal Transition Study presents initial findings on individual characteristics which relate to postsecondary education participation since 1985-86 among more than 8,000 youth (ages 13 to 23) with disabilities. A series of logistic regression models examines such factors as youth's background characteristics,…

MMI: Multimodel inference or models with management implications?

USGS Publications Warehouse

Fieberg, J.; Johnson, Douglas H.

2015-01-01

We consider a variety of regression modeling strategies for analyzing observational data associated with typical wildlife studies, including all subsets and stepwise regression, a single full model, and Akaike's Information Criterion (AIC)-based multimodel inference. Although there are advantages and disadvantages to each approach, we suggest that there is no unique best way to analyze data. Further, we argue that, although multimodel inference can be useful in natural resource management, the importance of considering causality and accurately estimating effect sizes is greater than simply considering a variety of models. Determining causation is far more valuable than simply indicating how the response variable and explanatory variables covaried within a data set, especially when the data set did not arise from a controlled experiment. Understanding the causal mechanism will provide much better predictions beyond the range of data observed. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Logistic regression modeling to assess groundwater vulnerability to contamination in Hawaii, USA.

PubMed

Mair, Alan; El-Kadi, Aly I

2013-10-01

Capture zone analysis combined with a subjective susceptibility index is currently used in Hawaii to assess vulnerability to contamination of drinking water sources derived from groundwater. In this study, we developed an alternative objective approach that combines well capture zones with multiple-variable logistic regression (LR) modeling and applied it to the highly-utilized Pearl Harbor and Honolulu aquifers on the island of Oahu, Hawaii. Input for the LR models utilized explanatory variables based on hydrogeology, land use, and well geometry/location. A suite of 11 target contaminants detected in the region, including elevated nitrate (>1 mg/L), four chlorinated solvents, four agricultural fumigants, and two pesticides, was used to develop the models. We then tested the ability of the new approach to accurately separate groups of wells with low and high vulnerability, and the suitability of nitrate as an indicator of other types of contamination. Our results produced contaminant-specific LR models that accurately identified groups of wells with the lowest/highest reported detections and the lowest/highest nitrate concentrations. Current and former agricultural land uses were identified as significant explanatory variables for eight of the 11 target contaminants, while elevated nitrate was a significant variable for five contaminants. The utility of the combined approach is contingent on the availability of hydrologic and chemical monitoring data for calibrating groundwater and LR models. Application of the approach using a reference site with sufficient data could help identify key variables in areas with similar hydrogeology and land use but limited data. In addition, elevated nitrate may also be a suitable indicator of groundwater contamination in areas with limited data. The objective LR modeling approach developed in this study is flexible enough to address a wide range of contaminants and represents a suitable addition to the current subjective approach. © 2013 Elsevier B.V. All rights reserved.

Research of Water Level Prediction for a Continuous Flood due to Typhoons Based on a Machine Learning Method

NASA Astrophysics Data System (ADS)

Nakatsugawa, M.; Kobayashi, Y.; Okazaki, R.; Taniguchi, Y.

2017-12-01

This research aims to improve accuracy of water level prediction calculations for more effective river management. In August 2016, Hokkaido was visited by four typhoons, whose heavy rainfall caused severe flooding. In the Tokoro river basin of Eastern Hokkaido, the water level (WL) at the Kamikawazoe gauging station, which is at the lower reaches exceeded the design high-water level and the water rose to the highest level on record. To predict such flood conditions and mitigate disaster damage, it is necessary to improve the accuracy of prediction as well as to prolong the lead time (LT) required for disaster mitigation measures such as flood-fighting activities and evacuation actions by residents. There is the need to predict the river water level around the peak stage earlier and more accurately. Previous research dealing with WL prediction had proposed a method in which the WL at the lower reaches is estimated by the correlation with the WL at the upper reaches (hereinafter: "the water level correlation method"). Additionally, a runoff model-based method has been generally used in which the discharge is estimated by giving rainfall prediction data to a runoff model such as a storage function model and then the WL is estimated from that discharge by using a WL discharge rating curve (H-Q curve). In this research, an attempt was made to predict WL by applying the Random Forest (RF) method, which is a machine learning method that can estimate the contribution of explanatory variables. Furthermore, from the practical point of view, we investigated the prediction of WL based on a multiple correlation (MC) method involving factors using explanatory variables with high contribution in the RF method, and we examined the proper selection of explanatory variables and the extension of LT. The following results were found: 1) Based on the RF method tuned up by learning from previous floods, the WL for the abnormal flood case of August 2016 was properly predicted with a lead time of 6 h. 2) Based on the contribution of explanatory variables, factors were selected for the MC method. In this way, plausible prediction results were obtained.

Sociobiology for Social Scientists: A Critical Introduction to E.O. Wilson's Evolutionary Paradigm.

ERIC Educational Resources Information Center

Dugger, William M.

1981-01-01

Reviews recent works of E.O. Wilson on sociobiology (the evolutionary and comparative study of social animals, including humans). Topics discussed include the nature of sociobiology, explanatory hypotheses in sociobiology, subdisciplines, biological individualism and altruism, costs of social engineering, and evolutionary perspectives. (DB)

Design of an impact evaluation using a mixed methods model--an explanatory assessment of the effects of results-based financing mechanisms on maternal healthcare services in Malawi.

PubMed

Brenner, Stephan; Muula, Adamson S; Robyn, Paul Jacob; Bärnighausen, Till; Sarker, Malabika; Mathanga, Don P; Bossert, Thomas; De Allegri, Manuela

2014-04-22

In this article we present a study design to evaluate the causal impact of providing supply-side performance-based financing incentives in combination with a demand-side cash transfer component on equitable access to and quality of maternal and neonatal healthcare services. This intervention is introduced to selected emergency obstetric care facilities and catchment area populations in four districts in Malawi. We here describe and discuss our study protocol with regard to the research aims, the local implementation context, and our rationale for selecting a mixed methods explanatory design with a quasi-experimental quantitative component. The quantitative research component consists of a controlled pre- and post-test design with multiple post-test measurements. This allows us to quantitatively measure 'equitable access to healthcare services' at the community level and 'healthcare quality' at the health facility level. Guided by a theoretical framework of causal relationships, we determined a number of input, process, and output indicators to evaluate both intended and unintended effects of the intervention. Overall causal impact estimates will result from a difference-in-difference analysis comparing selected indicators across intervention and control facilities/catchment populations over time.To further explain heterogeneity of quantitatively observed effects and to understand the experiential dimensions of financial incentives on clients and providers, we designed a qualitative component in line with the overall explanatory mixed methods approach. This component consists of in-depth interviews and focus group discussions with providers, service user, non-users, and policy stakeholders. In this explanatory design comprehensive understanding of expected and unexpected effects of the intervention on both access and quality will emerge through careful triangulation at two levels: across multiple quantitative elements and across quantitative and qualitative elements. Combining a traditional quasi-experimental controlled pre- and post-test design with an explanatory mixed methods model permits an additional assessment of organizational and behavioral changes affecting complex processes. Through this impact evaluation approach, our design will not only create robust evidence measures for the outcome of interest, but also generate insights on how and why the investigated interventions produce certain intended and unintended effects and allows for a more in-depth evaluation approach.

Examining Explanatory Style's Relationship to Efficacy and Burnout in Teachers

ERIC Educational Resources Information Center

Fineburg, Amy Cheek

2010-01-01

Explanatory style, the ways in which people explain both good and bad events (Seligman, 1998), shares theoretical components with teachers' sense of efficacy (Tshannon-Moran & Woolfolk-Hoy, 2001), which is how capable teachers feel about teaching. According to Bandura (1994), efficacy informs explanatory style, but this assertion does not…

A study of low-cost reliable actuators for light aircraft. Part B: Appendices

NASA Technical Reports Server (NTRS)

Eijsink, H.; Rice, M.

1978-01-01

Computer programs written in FORTRAN are given for time response calculations on pneumatic and linear hydraulic actuators. The programs are self-explanatory with comment statements. Program output is also included.

Management practices associated with conception rate and service rate of lactating Holstein cows in large, commercial dairy herds.

PubMed

Schefers, J M; Weigel, K A; Rawson, C L; Zwald, N R; Cook, N B

2010-04-01

Data from lactating Holstein cows in herds that participate in a commercial progeny testing program were analyzed to explain management factors associated with herd-average conception and service rates on large commercial dairies. On-farm herd management software was used as the source of data related to production, reproduction, culling, and milk quality for 108 herds. Also, a survey regarding management, facilities, nutrition, and labor was completed on 86 farms. A total of 41 explanatory variables related to management factors and conditions that could affect conception and service rate were considered in this study. Models explaining conception and service rates were developed using a machine learning algorithm for constructing model trees. The most important explanatory variables associated with conception rate were the percentage of repeated inseminations between 4 and 17 d post-artificial insemination, stocking density in the breeding pen, length of the voluntary waiting period, days at pregnancy examination, and somatic cell score. The most important explanatory variables associated with service rate were the number of lactating cows per breeding technician, use of a resynchronization program, utilization of soakers in the holding area during the summer, and bunk space per cow in the breeding pen. The aforementioned models explained 35% and 40% of the observed variation in conception rate and service rate, respectively, and underline the association of herd-level management factors not strictly related to reproduction with herd reproductive performance. Copyright (c) 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Multiscale Framework for Assessing Critical Loads of Atmospheric Nitrogen Deposition for Aquatic Ecosystems in Wilderness Areas of the Western United States

NASA Astrophysics Data System (ADS)

Nanus, Leora; Clow, David; Saros, Jasmine; McMurray, Jill; Blett, Tamara; Sickman, James

2017-04-01

High-elevation aquatic ecosystems in Wilderness areas of the western United States are impacted by current and historic atmospheric nitrogen (N) deposition associated with local and regional air pollution. Documented effects include elevated surface water nitrate concentrations, increased algal productivity, and changes in diatom species assemblages. A predictive framework was developed for sensitive high-elevation basins across the western United States at multiple spatial scales including the Rocky Mountain Region (Rockies), the Greater Yellowstone Area (GYA), and Yosemite (YOSE) and Sequoia & Kings Canyon (SEKI) National Parks. Spatial trends in critical loads of N deposition for nutrient enrichment of aquatic ecosystems were quantified and mapped using a geostatistical approach, with modeled N deposition, topography, vegetation, geology, and climate as potential explanatory variables. Multiple predictive models were created using various combinations of explanatory variables; this approach allowed for better quantification of uncertainty and identification of areas most sensitive to high atmospheric N deposition (> 3 kg N ha-1 yr-1). For multiple spatial scales, the lowest critical loads estimates (<1.5 + 1 kg N ha-1 yr-1) occurred in high-elevation basins with steep slopes, sparse vegetation, and exposed bedrock and talus. Based on a nitrate threshold of 1 μmol L-1, estimated critical load exceedances (>1.5 + 1 kg N ha-1 yr-1) correspond with areas of high N deposition and vary spatially ranging from less than 20% to over 40% of the study area for the Rockies, GYA, YOSE, and SEKI. These predictive models and maps identify sensitive aquatic ecosystems that may be impacted by excess atmospheric N deposition and can be used to help protect against future anthropogenic disturbance. The approach presented here may be transferable to other remote and protected high-elevation ecosystems at multiple spatial scales that are sensitive to adverse effects of pollutant loading in the US and around the world.

Illness perceptions and explanatory models of viral hepatitis B & C among immigrants and refugees: a narrative systematic review.

PubMed

Owiti, John A; Greenhalgh, Trisha; Sweeney, Lorna; Foster, Graham R; Bhui, Kamaldeep S

2015-02-15

Hepatitis B and C (HBV, HCV) infections are associated with high morbidity and mortality. Many countries with traditionally low prevalence (such as UK) are now planning interventions (screening, vaccination, and treatment) of high-risk immigrants from countries with high prevalence. This review aimed to synthesise the evidence on immigrants' knowledge of HBV and HCV that might influence the uptake of clinical interventions. The review was also used to inform the design and successful delivery of a randomised controlled trial of targeted screening and treatment. Five databases (PubMed, CINHAL, SOCIOFILE, PsycINFO & Web of Science) were systematically searched, supplemented by reference tracking, searches of selected journals, and of relevant websites. We aimed to identify qualitative and quantitative studies that investigated knowledge of HBV and HCV among immigrants from high endemic areas to low endemic areas. Evidence, extracted according to a conceptual framework of Kleinman's explanatory model, was subjected to narrative synthesis. We adapted the PEN-3 model to categorise and analyse themes, and recommend strategies for interventions to influence help-seeking behaviour. We identified 51 publications including quantitative (n = 39), qualitative (n = 11), and mixed methods (n = 1) designs. Most of the quantitative studies included small samples and had heterogeneous methods and outcomes. The studies mainly concentrated on hepatitis B and ethnic groups of South East Asian immigrants residing in USA, Canada, and Australia. Many immigrants lacked adequate knowledge of aetiology, symptoms, transmission risk factors, prevention strategies, and treatment, of hepatitis HBV and HCV. Ethnicity, gender, better education, higher income, and English proficiency influenced variations in levels and forms of knowledge. Immigrants are vulnerable to HBV and HCV, and risk life-threatening complications from these infections because of poor knowledge and help-seeking behaviour. Primary studies in this area are extremely diverse and of variable quality precluding meta-analysis. Further research is needed outside North America and Australia.

Overdose beliefs and management practices among ethnic Vietnamese heroin users in Sydney, Australia

PubMed Central

Maher, Lisa; Ho, Hien T

2009-01-01

Background Ethnic Vietnamese injecting drug users (IDUs) in Australia draw on a range of beliefs and etiologic models, sometimes simultaneously, in order to make sense of health and illness. These include understandings of illness as the result of internal imbalances and Western concepts of disease causation including germ/pollution theory. Methods Observational fieldwork and in-depth interviews were conducted between 2001 and 2006 in neighbourhoods characterised by high proportions of Asian background IDUs and street-based drug markets. Eligibility criteria for the study were: 1) ethnic Vietnamese cultural background; 2) aged 16 years and over and; 3) injected drugs in the last 6 months. Results Participants commonly attempted to treat heroin overdose by withdrawing blood (rút máu) from the body. Central to this practice are cultural beliefs about the role and function of blood in the body and its relationship to illness and health. Participants' beliefs in blood were strongly influenced by understandings of blood expressed in traditional Chinese and Vietnamese medicine. Many participants perceived Western drugs, particularly heroin, as "hot" and "strong". In overdose situations, it was commonly believed that an excessive amount of drugs (particularly heroin) entered the bloodstream and traveled to the heart, making the heart work too hard. Withdrawing blood was understood to reduce the amount of drugs in the body which in turn reduced the effects of drugs on the blood and the heart. Conclusion The explanatory model of overdose employed by ethnic Vietnamese IDUs privileges traditional beliefs about the circulatory, rather than the respiratory, system. This paper explores participants' beliefs about blood, the effects of drugs on blood and the causes of heroin overdose in order to document the explanatory model of overdose used by ethnic Vietnamese IDUs. Implications for overdose prevention, treatment and management are identified and discussed. PMID:19397811

Online Statistical Modeling (Regression Analysis) for Independent Responses

NASA Astrophysics Data System (ADS)

Made Tirta, I.; Anggraeni, Dian; Pandutama, Martinus

2017-06-01

Regression analysis (statistical analmodelling) are among statistical methods which are frequently needed in analyzing quantitative data, especially to model relationship between response and explanatory variables. Nowadays, statistical models have been developed into various directions to model various type and complex relationship of data. Rich varieties of advanced and recent statistical modelling are mostly available on open source software (one of them is R). However, these advanced statistical modelling, are not very friendly to novice R users, since they are based on programming script or command line interface. Our research aims to developed web interface (based on R and shiny), so that most recent and advanced statistical modelling are readily available, accessible and applicable on web. We have previously made interface in the form of e-tutorial for several modern and advanced statistical modelling on R especially for independent responses (including linear models/LM, generalized linier models/GLM, generalized additive model/GAM and generalized additive model for location scale and shape/GAMLSS). In this research we unified them in the form of data analysis, including model using Computer Intensive Statistics (Bootstrap and Markov Chain Monte Carlo/ MCMC). All are readily accessible on our online Virtual Statistics Laboratory. The web (interface) make the statistical modeling becomes easier to apply and easier to compare them in order to find the most appropriate model for the data.

An explanatory model of academic achievement based on aptitudes, goal orientations, self-concept and learning strategies.

PubMed

Miñano Pérez, Pablo; Castejón Costa, Juan-Luis; Gilar Corbí, Raquel

2012-03-01

As a result of studies examining factors involved in the learning process, various structural models have been developed to explain the direct and indirect effects that occur between the variables in these models. The objective was to evaluate a structural model of cognitive and motivational variables predicting academic achievement, including general intelligence, academic self-concept, goal orientations, effort and learning strategies. The sample comprised of 341 Spanish students in the first year of compulsory secondary education. Different tests and questionnaires were used to evaluate each variable, and Structural Equation Modelling (SEM) was applied to contrast the relationships of the initial model. The model proposed had a satisfactory fit, and all the hypothesised relationships were significant. General intelligence was the variable most able to explain academic achievement. Also important was the direct influence of academic self-concept on achievement, goal orientations and effort, as well as the mediating ability of effort and learning strategies between academic goals and final achievement.

Mixed-effects Gaussian process functional regression models with application to dose-response curve prediction.

PubMed

Shi, J Q; Wang, B; Will, E J; West, R M

2012-11-20

We propose a new semiparametric model for functional regression analysis, combining a parametric mixed-effects model with a nonparametric Gaussian process regression model, namely a mixed-effects Gaussian process functional regression model. The parametric component can provide explanatory information between the response and the covariates, whereas the nonparametric component can add nonlinearity. We can model the mean and covariance structures simultaneously, combining the information borrowed from other subjects with the information collected from each individual subject. We apply the model to dose-response curves that describe changes in the responses of subjects for differing levels of the dose of a drug or agent and have a wide application in many areas. We illustrate the method for the management of renal anaemia. An individual dose-response curve is improved when more information is included by this mechanism from the subject/patient over time, enabling a patient-specific treatment regime. Copyright © 2012 John Wiley & Sons, Ltd.

Ecological and cosmological coexistence thinking in a hypervariable environment: causal models of economic success and failure among farmers, foragers, and fishermen of southwestern Madagascar

PubMed Central

Tucker, Bram; Tsiazonera; Tombo, Jaovola; Hajasoa, Patricia; Nagnisaha, Charlotte

2015-01-01

A fact of life for farmers, hunter-gatherers, and fishermen in the rural parts of the world are that crops fail, wild resources become scarce, and winds discourage fishing. In this article we approach subsistence risk from the perspective of “coexistence thinking,” the simultaneous application of natural and supernatural causal models to explain subsistence success and failure. In southwestern Madagascar, the ecological world is characterized by extreme variability and unpredictability, and the cosmological world is characterized by anxiety about supernatural dangers. Ecological and cosmological causes seem to point to different risk minimizing strategies: to avoid losses from drought, flood, or heavy winds, one should diversify activities and be flexible; but to avoid losses caused by disrespected spirits one should narrow one’s range of behaviors to follow the code of taboos and offerings. We address this paradox by investigating whether southwestern Malagasy understand natural and supernatural causes as occupying separate, contradictory explanatory systems (target dependence), whether they make no categorical distinction between natural and supernatural forces and combine them within a single explanatory system (synthetic thinking), or whether they have separate natural and supernatural categories of causes that are integrated into one explanatory system so that supernatural forces drive natural forces (integrative thinking). Results from three field studies suggest that (a) informants explain why crops, prey, and market activities succeed or fail with reference to natural causal forces like rainfall and pests, (b) they explain why individual persons experience success or failure primarily with supernatural factors like God and ancestors, and (c) they understand supernatural forces as driving natural forces, so that ecology and cosmology represent distinct sets of causes within a single explanatory framework. We expect that future cross-cultural analyses may find that this form of “integrative thinking” is common in unpredictable environments and is a cognitive strategy that accompanies economic diversification. PMID:26528205

Ecological and cosmological coexistence thinking in a hypervariable environment: causal models of economic success and failure among farmers, foragers, and fishermen of southwestern Madagascar.

PubMed

Tucker, Bram; Tsiazonera; Tombo, Jaovola; Hajasoa, Patricia; Nagnisaha, Charlotte

2015-01-01

A fact of life for farmers, hunter-gatherers, and fishermen in the rural parts of the world are that crops fail, wild resources become scarce, and winds discourage fishing. In this article we approach subsistence risk from the perspective of "coexistence thinking," the simultaneous application of natural and supernatural causal models to explain subsistence success and failure. In southwestern Madagascar, the ecological world is characterized by extreme variability and unpredictability, and the cosmological world is characterized by anxiety about supernatural dangers. Ecological and cosmological causes seem to point to different risk minimizing strategies: to avoid losses from drought, flood, or heavy winds, one should diversify activities and be flexible; but to avoid losses caused by disrespected spirits one should narrow one's range of behaviors to follow the code of taboos and offerings. We address this paradox by investigating whether southwestern Malagasy understand natural and supernatural causes as occupying separate, contradictory explanatory systems (target dependence), whether they make no categorical distinction between natural and supernatural forces and combine them within a single explanatory system (synthetic thinking), or whether they have separate natural and supernatural categories of causes that are integrated into one explanatory system so that supernatural forces drive natural forces (integrative thinking). Results from three field studies suggest that (a) informants explain why crops, prey, and market activities succeed or fail with reference to natural causal forces like rainfall and pests, (b) they explain why individual persons experience success or failure primarily with supernatural factors like God and ancestors, and (c) they understand supernatural forces as driving natural forces, so that ecology and cosmology represent distinct sets of causes within a single explanatory framework. We expect that future cross-cultural analyses may find that this form of "integrative thinking" is common in unpredictable environments and is a cognitive strategy that accompanies economic diversification.

Validation of an explanatory tool for data-fused displays for high-technology future aircraft

NASA Astrophysics Data System (ADS)

Fletcher, Georgina C. L.; Shanks, Craig R.; Selcon, Stephen J.

1996-05-01

As the number of sensor and data sources in the military cockpit increases, pilots will suffer high levels of workload which could result in reduced performance and the loss of situational awareness. A DRA research program has been investigating the use of data-fused displays in decision support and has developed and laboratory-tested an explanatory tool for displaying information in air combat scenarios. The tool has been designed to provide pictorial explanations of data that maintain situational awareness by involving the pilot in the hostile aircraft threat assessment task. This paper reports a study carried out to validate the success of the explanatory tool in a realistic flight simulation facility. Aircrew were asked to perform a threat assessment task, either with or without the explanatory tool providing information in the form of missile launch success zone envelopes, while concurrently flying a waypoint course within set flight parameters. The results showed that there was a significant improvement (p less than 0.01) in threat assessment accuracy of 30% when using the explanatory tool. This threat assessment performance advantage was achieved without a trade-off with flying task performance. Situational awareness measures showed no general differences between the explanatory and control conditions, but significant learning effects suggested that the explanatory tool makes the task initially more intuitive and hence less demanding on the pilots' attentional resources. The paper concludes that DRA's data-fused explanatory tool is successful at improving threat assessment accuracy in a realistic simulated flying environment, and briefly discusses the requirements for further research in the area.

Mechanisms of eyewitness suggestibility: tests of the explanatory role hypothesis.

PubMed

Rindal, Eric J; Chrobak, Quin M; Zaragoza, Maria S; Weihing, Caitlin A

2017-10-01

In a recent paper, Chrobak and Zaragoza (Journal of Experimental Psychology: General, 142(3), 827-844, 2013) proposed the explanatory role hypothesis, which posits that the likelihood of developing false memories for post-event suggestions is a function of the explanatory function the suggestion serves. In support of this hypothesis, they provided evidence that participant-witnesses were especially likely to develop false memories for their forced fabrications when their fabrications helped to explain outcomes they had witnessed. In three experiments, we test the generality of the explanatory role hypothesis as a mechanism of eyewitness suggestibility by assessing whether this hypothesis can predict suggestibility errors in (a) situations where the post-event suggestions are provided by the experimenter (as opposed to fabricated by the participant), and (b) across a variety of memory measures and measures of recollective experience. In support of the explanatory role hypothesis, participants were more likely to subsequently freely report (E1) and recollect the suggestions as part of the witnessed event (E2, source test) when the post-event suggestion helped to provide a causal explanation for a witnessed outcome than when it did not serve this explanatory role. Participants were also less likely to recollect the suggestions as part of the witnessed event (on measures of subjective experience) when their explanatory strength had been reduced by the presence of an alternative explanation that could explain the same outcome (E3, source test + warning). Collectively, the results provide strong evidence that the search for explanatory coherence influences people's tendency to misremember witnessing events that were only suggested to them.

Student Misapplication of a Gas-Like Model to Explain Particle Movement in Heated Solids: Implications for Curriculum and Instruction towards Students' Creation and Revision of Accurate Explanatory Models

ERIC Educational Resources Information Center

Bouwma-Gearhart, Jana; Stewart, James; Brown, Keffrelyn

2009-01-01

Understanding the particulate nature of matter (PNM) is vital for participating in many areas of science. We assessed 11 students' atomic/molecular-level explanations of real-world phenomena after their participation in a modelling-based PNM unit. All 11 students offered a scientifically acceptable model regarding atomic/molecular behaviour in…

A multimodal dataset for various forms of distracted driving

PubMed Central

Taamneh, Salah; Tsiamyrtzis, Panagiotis; Dcosta, Malcolm; Buddharaju, Pradeep; Khatri, Ashik; Manser, Michael; Ferris, Thomas; Wunderlich, Robert; Pavlidis, Ioannis

2017-01-01

We describe a multimodal dataset acquired in a controlled experiment on a driving simulator. The set includes data for n=68 volunteers that drove the same highway under four different conditions: No distraction, cognitive distraction, emotional distraction, and sensorimotor distraction. The experiment closed with a special driving session, where all subjects experienced a startle stimulus in the form of unintended acceleration—half of them under a mixed distraction, and the other half in the absence of a distraction. During the experimental drives key response variables and several explanatory variables were continuously recorded. The response variables included speed, acceleration, brake force, steering, and lane position signals, while the explanatory variables included perinasal electrodermal activity (EDA), palm EDA, heart rate, breathing rate, and facial expression signals; biographical and psychometric covariates as well as eye tracking data were also obtained. This dataset enables research into driving behaviors under neatly abstracted distracting stressors, which account for many car crashes. The set can also be used in physiological channel benchmarking and multispectral face recognition. PMID:28809848

Axial cervical vertebrae-based multivariate regression model for the estimation of skeletal-maturation status.

PubMed

Yang, Y-M; Lee, J; Kim, Y-I; Cho, B-H; Park, S-B

2014-08-01

This study aimed to determine the viability of using axial cervical vertebrae (ACV) as biological indicators of skeletal maturation and to build models that estimate ossification level with improved explanatory power over models based only on chronological age. The study population comprised 74 female and 47 male patients with available hand-wrist radiographs and cone-beam computed tomography images. Generalized Procrustes analysis was used to analyze the shape, size, and form of the ACV regions of interest. The variabilities of these factors were analyzed by principal component analysis. Skeletal maturation was then estimated using a multiple regression model. Separate models were developed for male and female participants. For the female estimation model, the adjusted R(2) explained 84.8% of the variability of the Sempé maturation level (SML), representing a 7.9% increase in SML explanatory power over that using chronological age alone (76.9%). For the male estimation model, the adjusted R(2) was over 90%, representing a 1.7% increase relative to the reference model. The simplest possible ACV morphometric information provided a statistically significant explanation of the portion of skeletal-maturation variability not dependent on chronological age. These results verify that ACV is a strong biological indicator of ossification status. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Children with Autism Spectrum Disorder Have an Exceptional Explanatory Drive

ERIC Educational Resources Information Center

Rutherford, M. D.; Subiaul, Francys

2016-01-01

An "explanatory drive" motivates children to explain ambiguity. Individuals with autism spectrum disorders are interested in how systems work, but it is unknown whether they have an explanatory drive. We presented children with and without autism spectrum disorder unsolvable problems in a physical and in a social context and evaluated…

Academic Judgment and Institutional Evaluation Made by Teachers According to Pupils' Explanatory Activity

ERIC Educational Resources Information Center

Jouffre, Stephane; Py, Jacques; Somat, Alain

2008-01-01

The influence of sixth-graders' explanatory activity was studied on their teachers' academic judgment. Concerning the pupils' explanatory activity, trait-related internal explanations were chosen more to explain positive events than negative ones, whereas the reverse was observed for effort/intention-related internal explanations. In response to…

Explanatory Typologies as a Nested Strategy of Inquiry: Combining Cross-Case and Within-Case Analyses

ERIC Educational Resources Information Center

Møller, Jørgen; Skaaning, Svend-Erik

2017-01-01

Explanatory typologies have recently experienced a renaissance as a research strategy for constructing and assessing causal explanations. However, both the new methodological works on explanatory typologies and the way such typologies have been used in practice have been affected by two shortcomings. First, no elaborate procedures for assessing…

Joint perceptual decision-making: a case study in explanatory pluralism

PubMed Central

Abney, Drew H.; Dale, Rick; Yoshimi, Jeff; Kello, Chris T.; Tylén, Kristian; Fusaroli, Riccardo

2014-01-01

Traditionally different approaches to the study of cognition have been viewed as competing explanatory frameworks. An alternative view, explanatory pluralism, regards different approaches to the study of cognition as complementary ways of studying the same phenomenon, at specific temporal and spatial scales, using appropriate methodological tools. Explanatory pluralism has been often described abstractly, but has rarely been applied to concrete cases. We present a case study of explanatory pluralism. We discuss three separate ways of studying the same phenomenon: a perceptual decision-making task (Bahrami et al., 2010), where pairs of subjects share information to jointly individuate an oddball stimulus among a set of distractors. Each approach analyzed the same corpus but targeted different units of analysis at different levels of description: decision-making at the behavioral level, confidence sharing at the linguistic level, and acoustic energy at the physical level. We discuss the utility of explanatory pluralism for describing this complex, multiscale phenomenon, show ways in which this case study sheds new light on the concept of pluralism, and highlight good practices to critically assess and complement approaches. PMID:24795679

Long-term change in a behavioural trait: truncated spawning distribution and demography in Northeast Arctic cod

PubMed Central

Opdal, Anders Frugård; Jørgensen, Christian

2015-01-01

Harvesting may be a potent driver of demographic change and contemporary evolution, which both may have great impacts on animal populations. Research has focused on changes in phenotypic traits that are easily quantifiable and for which time series exist, such as size, age, sex, or gonad size, whereas potential changes in behavioural traits have been under-studied. Here, we analyse potential drivers of long-term changes in a behavioural trait for the Northeast Arctic stock of Atlantic cod Gadus morhua, namely choice of spawning location. For 104 years (1866–1969), commercial catches were recorded annually and reported by county along the Norwegian coast. During this time period, spawning ground distribution has fluctuated with a trend towards more northerly spawning. Spawning location is analysed against a suite of explanatory factors including climate, fishing pressure, density dependence, and demography. We find that demography (age or age at maturation) had the highest explanatory power for variation in spawning location, while climate had a limited effect below statistical significance. As to potential mechanisms, some effects of climate may act through demography, and explanatory variables for demography may also have absorbed direct evolutionary change in migration distance for which proxies were unavailable. Despite these caveats, we argue that fishing mortality, either through demographic or evolutionary change, has served as an effective driver for changing spawning locations in cod, and that additional explanatory factors related to climate add no significant information. PMID:25336028

75 FR 26714 - Proposed Information Collection; Comment Request; Application for Designation of a Fair

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-12

... articles which may be brought in, include, but are not limited to, actual exhibit items, pamphlets, brochures, and explanatory material in reasonable quantities relating to the foreign exhibits at a trade...

A Theory-Based Model for Understanding Faculty Intention to Use Students Ratings to Improve Teaching in a Health Sciences Institution in Puerto Rico

ERIC Educational Resources Information Center

Collazo, Andrés A.

2018-01-01

A model derived from the theory of planned behavior was empirically assessed for understanding faculty intention to use student ratings for teaching improvement. A sample of 175 professors participated in the study. The model was statistically significant and had a very large explanatory power. Instrumental attitude, affective attitude, perceived…

Progressive Transitions from Algorithmic to Conceptual Understanding in Student Ability To Solve Chemistry Problems: A Lakatosian Interpretation.

ERIC Educational Resources Information Center

Niaz, Mansoor

The main objective of this study is to construct models based on strategies students use to solve chemistry problems and to show that these models form sequences of progressive transitions similar to what Lakatos (1970) in the history of science refers to as progressive 'problemshifts' that increase the explanatory' heuristic power of the models.…

Anxiety Psychopathology in African American Adults: Literature Review and Development of an Empirically Informed Sociocultural Model

ERIC Educational Resources Information Center

Hunter, Lora Rose; Schmidt, Norman B.

2010-01-01

In this review, the extant literature concerning anxiety psychopathology in African American adults is summarized to develop a testable, explanatory framework with implications for future research. The model was designed to account for purported lower rates of anxiety disorders in African Americans compared to European Americans, along with other…

Using Vygotsky's Zone of Proximal Development to Propose and Test an Explanatory Model for Conceptualising Coteaching in Pre-Service Science Teacher Education

ERIC Educational Resources Information Center

Murphy, Colette; Scantlebury, Kathryn; Milne, Catherine

2015-01-01

Coteaching offers a model for the school-placement element of pre-service science teacher education, based on its demonstrated positive impacts on lessening classroom anxiety, supporting inquiry-based science teaching, improving students' attitudes, and addressing diversity effectively in science classrooms. Coteaching between pre-service and…

Model of Values-Based Management Process in Schools: A Mixed Design Study

ERIC Educational Resources Information Center

Dogan, Soner

2016-01-01

The aim of this paper is to evaluate the school administrators' values-based management behaviours according to the teachers' perceptions and opinions and, accordingly, to build a model of values-based management process in schools. The study was conducted using explanatory design which is inclusive of both quantitative and qualitative methods.…

Integrating Behavioral-Motive and Experiential-Requirement Perspectives on Psychological Needs: A Two Process Model

ERIC Educational Resources Information Center

Sheldon, Kennon M.

2011-01-01

Psychological need theories offer much explanatory potential for behavioral scientists, but there is considerable disagreement and confusion about what needs are and how they work. A 2-process model of psychological needs is outlined, viewing needs as evolved functional systems that provide both (a) innate psychosocial motives that tend to impel…

Using a Modeling Approach To Explore Scientific Epistemology with High School Biology Students. Research Report.

ERIC Educational Resources Information Center

Cartier, Jennifer

This paper describes a study of high school students' participation in the construction and revision of explanatory models as they attempted to account for a variety of inheritance phenomena observed in computer-generated "fruit flies". Throughout the course students were encouraged to explore epistemological issues related to the assessment and…

Improving Explanatory Inferences from Assessments

ERIC Educational Resources Information Center

Diakow, Ronli Phyllis

2013-01-01

This dissertation comprises three papers that propose, discuss, and illustrate models to make improved inferences about research questions regarding student achievement in education. Addressing the types of questions common in educational research today requires three different "extensions" to traditional educational assessment: (1)…

Determinants of Judgments of Explanatory Power: Credibility, Generality, and Statistical Relevance.

PubMed

Colombo, Matteo; Bucher, Leandra; Sprenger, Jan

2017-01-01

Explanation is a central concept in human psychology. Drawing upon philosophical theories of explanation, psychologists have recently begun to examine the relationship between explanation, probability and causality. Our study advances this growing literature at the intersection of psychology and philosophy of science by systematically investigating how judgments of explanatory power are affected by (i) the prior credibility of an explanatory hypothesis, (ii) the causal framing of the hypothesis, (iii) the perceived generalizability of the explanation, and (iv) the relation of statistical relevance between hypothesis and evidence. Collectively, the results of our five experiments support the hypothesis that the prior credibility of a causal explanation plays a central role in explanatory reasoning: first, because of the presence of strong main effects on judgments of explanatory power, and second, because of the gate-keeping role it has for other factors. Highly credible explanations are not susceptible to causal framing effects, but they are sensitive to the effects of normatively relevant factors: the generalizability of an explanation, and its statistical relevance for the evidence. These results advance current literature in the philosophy and psychology of explanation in three ways. First, they yield a more nuanced understanding of the determinants of judgments of explanatory power, and the interaction between these factors. Second, they show the close relationship between prior beliefs and explanatory power. Third, they elucidate the nature of abductive reasoning.

Determinants of Judgments of Explanatory Power: Credibility, Generality, and Statistical Relevance

PubMed Central

Colombo, Matteo; Bucher, Leandra; Sprenger, Jan

2017-01-01

Explanation is a central concept in human psychology. Drawing upon philosophical theories of explanation, psychologists have recently begun to examine the relationship between explanation, probability and causality. Our study advances this growing literature at the intersection of psychology and philosophy of science by systematically investigating how judgments of explanatory power are affected by (i) the prior credibility of an explanatory hypothesis, (ii) the causal framing of the hypothesis, (iii) the perceived generalizability of the explanation, and (iv) the relation of statistical relevance between hypothesis and evidence. Collectively, the results of our five experiments support the hypothesis that the prior credibility of a causal explanation plays a central role in explanatory reasoning: first, because of the presence of strong main effects on judgments of explanatory power, and second, because of the gate-keeping role it has for other factors. Highly credible explanations are not susceptible to causal framing effects, but they are sensitive to the effects of normatively relevant factors: the generalizability of an explanation, and its statistical relevance for the evidence. These results advance current literature in the philosophy and psychology of explanation in three ways. First, they yield a more nuanced understanding of the determinants of judgments of explanatory power, and the interaction between these factors. Second, they show the close relationship between prior beliefs and explanatory power. Third, they elucidate the nature of abductive reasoning. PMID:28928679

Modeling Traffic on the Web Graph

NASA Astrophysics Data System (ADS)

Meiss, Mark R.; Gonçalves, Bruno; Ramasco, José J.; Flammini, Alessandro; Menczer, Filippo

Analysis of aggregate and individual Web requests shows that PageRank is a poor predictor of traffic. We use empirical data to characterize properties of Web traffic not reproduced by Markovian models, including both aggregate statistics such as page and link traffic, and individual statistics such as entropy and session size. As no current model reconciles all of these observations, we present an agent-based model that explains them through realistic browsing behaviors: (1) revisiting bookmarked pages; (2) backtracking; and (3) seeking out novel pages of topical interest. The resulting model can reproduce the behaviors we observe in empirical data, especially heterogeneous session lengths, reconciling the narrowly focused browsing patterns of individual users with the extreme variance in aggregate traffic measurements. We can thereby identify a few salient features that are necessary and sufficient to interpret Web traffic data. Beyond the descriptive and explanatory power of our model, these results may lead to improvements in Web applications such as search and crawling.

Critical Loads of Atmospheric Nitrogen Deposition for Aquatic Ecosystems in Yosemite and Sequoia and Kings Canyon National Parks

NASA Astrophysics Data System (ADS)

Nanus, L.; Clow, D. W.; Sickman, J. O.

2016-12-01

High-elevation aquatic ecosystems in Yosemite (YOSE) and Sequoia and Kings Canyon (SEKI) National Parks are impacted by atmospheric nitrogen (N) deposition associated with local and regional air pollution. Documented effects include elevated surface water nitrate concentrations, increased algal productivity, and changes in diatom species assemblages. Annual wet inorganic N deposition maps, developed at 1-km resolution for YOSE and SEKI to quantify N deposition to sensitive high-elevation ecosystems, range from 1.0 to over 5.0 kg N ha-1 yr-1. Critical loads of N deposition for nutrient enrichment of aquatic ecosystems were quantified and mapped using a geostatistical approach, with N deposition, topography, vegetation, geology, and climate as potential explanatory variables. Multiple predictive models were created using various combinations of explanatory variables; this approach allowed us to better quantify uncertainty and more accurately identify the areas most sensitive to atmospherically deposited N. The lowest critical loads estimates and highest exceedances identified within YOSE and SEKI occurred in high-elevation basins with steep slopes, sparse vegetation, and areas of neoglacial till and talus. These results are consistent with previous analyses in the Rocky Mountains, and highlight the sensitivity of alpine ecosystems to atmospheric N deposition.

Fighting fair: Adaptive Marital Conflict Strategies as Predictors of Future Adolescent Peer and Romantic Relationship Quality.

PubMed

Miga, Erin M; Gdula, Julie Ann; Allen, Joseph P

2012-08-01

This study examined the associations between reasoning during interparental conflict and autonomous adolescent conflict negotiation with peers over time. Participants included 133 adolescents and their parents, peers, and romantic partners in a multi-method, multiple reporter, longitudinal study. Interparental reasoning at adolescent age 13 predicted greater autonomy and relatedness in observed adolescent-peer conflict one year later and lower levels of autonomy undermining during observed romantic partner conflict five years later. Interparental reasoning also predicted greater satisfaction and affection in adolescent romantic relationships seven years later. Findings suggest that autonomy promoting behaviors exhibited in the interparental context may influence adolescents' own more autonomous approaches to subsequent peer and romantic conflict. Possible explanatory models are discussed, including social learning theory and attachment theory.

A data-centric approach to understanding the pricing of financial options

NASA Astrophysics Data System (ADS)

Healy, J.; Dixon, M.; Read, B.; Cai, F. F.

2002-05-01

We investigate what can be learned from a purely phenomenological study of options prices without modelling assumptions. We fitted neural net (NN) models to LIFFE ``ESX'' European style FTSE 100 index options using daily data from 1992 to 1997. These non-parametric models reproduce the Black-Scholes (BS) analytic model in terms of fit and performance measures using just the usual five inputs (S, X, t, r, IV). We found that adding transaction costs (bid-ask spread) to these standard five parameters gives a comparable fit and performance. Tests show that the bid-ask spread can be a statistically significant explanatory variable for option prices. The difference in option prices between the models with transaction costs and those without ranges from about -3.0 to +1.5 index points, varying with maturity date. However, the difference depends on the moneyness (S/X), being greatest in-the-money. This suggests that use of a five-factor model can result in a pricing difference of up to #10 to #30 per call option contract compared with modelling under transaction costs. We found that the influence of transaction costs varied between different yearly subsets of the data. Open interest is also a significant explanatory variable, but volume is not.

32 CFR Attachment 3 to Part 855 - Landing Permit Application Instructions

Code of Federal Regulations, 2010 CFR

2010-07-01

....13. Block 9c, Title. Self-explanatory. A3.1.14. Block 9d, Telephone Number. Self-explanatory. A3.1.15.... Block 3. Self-explanatory. (Users will not necessarily be denied landing rights if pilots are not... requested, it may be approved if warranted by unique circumstances. (The verification specified for each...

Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Sheyenne River, North Dakota, 1980-2006

USGS Publications Warehouse

Ryberg, Karen R.

2007-01-01

This report presents the results of a study by the U.S. Geological Survey, done in cooperation with the North Dakota State Water Commission, to estimate water-quality constituent concentrations at seven sites on the Sheyenne River, N. Dak. Regression analysis of water-quality data collected in 1980-2006 was used to estimate concentrations for hardness, dissolved solids, calcium, magnesium, sodium, and sulfate. The explanatory variables examined for the regression relations were continuously monitored streamflow, specific conductance, and water temperature. For the conditions observed in 1980-2006, streamflow was a significant explanatory variable for some constituents. Specific conductance was a significant explanatory variable for all of the constituents, and water temperature was not a statistically significant explanatory variable for any of the constituents in this study. The regression relations were evaluated using common measures of variability, including R2, the proportion of variability in the estimated constituent concentration explained by the explanatory variables and regression equation. R2 values ranged from 0.784 for calcium to 0.997 for dissolved solids. The regression relations also were evaluated by calculating the median relative percentage difference (RPD) between measured constituent concentration and the constituent concentration estimated by the regression equations. Median RPDs ranged from 1.7 for dissolved solids to 11.5 for sulfate. The regression relations also may be used to estimate daily constituent loads. The relations should be monitored for change over time, especially at sites 2 and 3 which have a short period of record. In addition, caution should be used when the Sheyenne River is affected by ice or when upstream sites are affected by isolated storm runoff. Almost all of the outliers and highly influential samples removed from the analysis were made during periods when the Sheyenne River might be affected by ice.

Sensitivity of Alpine and Subalpine Lakes to Atmospheric Deposition in Grand Teton National Park and Yellowstone National Park, Wyoming

NASA Astrophysics Data System (ADS)

Nanus, L.; Campbell, D. H.; Williams, M. W.

2004-12-01

Acidification of high-elevation lakes in the Western United States is of concern because of the storage and release of pollutants in snowmelt runoff combined with steep topography, granitic bedrock, and limited soils and biota. Land use managers have limited resources for sampling and thus need direction on how best to design monitoring programs. We evaluated the sensitivity of 400 lakes in Grand Teton (GRTE) and Yellowstone (YELL) National Parks to acidification from atmospheric deposition of nitrogen and sulfur based on statistical relations between acid-neutralizing capacity (ANC) concentrations and basin characteristics to aid in the design of a long-term monitoring plan for Outstanding Natural Resource Waters. ANC concentrations that were measured at 52 lakes in GRTE and 23 lakes in YELL during synoptic surveys were used to calibrate the statistical models. Basin-characteristic information was derived from Geographic Information System data sets. The explanatory variables that were considered included bedrock type, basin slope, basin aspect, basin elevation, lake area, basin area, inorganic nitrogen (N) deposition, sulfate deposition, hydrogen ion deposition, basin precipitation, soil type, and vegetation type. A logistic regression model was developed and applied to lake basins greater than 1 hectare (ha) in GRTE (n=106) and YELL (n=294). For GRTE, 36 percent of lakes had a greater than 60-percent probability of having ANC concentrations less than 100 microequivalents per liter, and 14 percent of lakes had a greater than 80-percent probability of having ANC concentrations less than 100 microequivalents per liter. The elevation of the lake outlet and the area of the basin with northeast aspects were determined to be statistically significant and were used as the explanatory variables in the multivariate logistic regression model. For YELL, results indicated that 13 percent of lakes had a greater than 60-percent probability of having ANC concentrations less than 100 microequivalents per liter, and 9 percent of lakes had a greater than 80-percent probability of having ANC concentrations less than 100 microequivalents per liter. Only the elevation of the lake outlet was determined to be statistically significant and was used as the explanatory variable in the multivariate logistic regression model. The lakes that exceeded 80-percent probability of having an ANC concentration less than 100 microequivalents per liter, and therefore had the greatest sensitivity to acidification from atmospheric deposition, are located at elevations greater than 2,810 meters (m) in GRTE, and greater than 2,655 m in YELL.

Attachment Security Balances Perspectives: Effects of Security Priming on Highly Optimistic and Pessimistic Explanatory Styles.

PubMed

Deng, Yanhe; Yan, Mengge; Chen, Henry; Sun, Xin; Zhang, Peng; Zeng, Xianglong; Liu, Xiangping; Lye, Yue

2016-01-01

Highly optimistic explanatory style (HOES) and highly pessimistic explanatory style (HPES) are two maladaptive ways to explain the world and may have roots in attachment insecurity. The current study aims to explore the effects of security priming - activating supportive representations of attachment security - on ameliorating these maladaptive explanatory styles. 57 participants with HOES and 57 participants with HPES were randomized into security priming and control conditions. Their scores of overall optimistic attribution were measured before and after priming. Security priming had a moderating effect: the security primed HOES group exhibited lower optimistic attribution, while the security primed HPES group evinced higher scores of optimistic attribution. Furthermore, the security primed HOES group attributed positive outcomes more externally, while the security primed HPES group attributed successful results more internally. The results support the application of security priming interventions on maladaptive explanatory styles. Its potential mechanism and directions for future study are also discussed.

Regression model development and computational procedures to support estimation of real-time concentrations and loads of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-9

USGS Publications Warehouse

Lee, Michael T.; Asquith, William H.; Oden, Timothy D.

2012-01-01

In December 2005, the U.S. Geological Survey (USGS), in cooperation with the City of Houston, Texas, began collecting discrete water-quality samples for nutrients, total organic carbon, bacteria (Escherichia coli and total coliform), atrazine, and suspended sediment at two USGS streamflow-gaging stations that represent watersheds contributing to Lake Houston (08068500 Spring Creek near Spring, Tex., and 08070200 East Fork San Jacinto River near New Caney, Tex.). Data from the discrete water-quality samples collected during 2005–9, in conjunction with continuously monitored real-time data that included streamflow and other physical water-quality properties (specific conductance, pH, water temperature, turbidity, and dissolved oxygen), were used to develop regression models for the estimation of concentrations of water-quality constituents of substantial source watersheds to Lake Houston. The potential explanatory variables included discharge (streamflow), specific conductance, pH, water temperature, turbidity, dissolved oxygen, and time (to account for seasonal variations inherent in some water-quality data). The response variables (the selected constituents) at each site were nitrite plus nitrate nitrogen, total phosphorus, total organic carbon, E. coli, atrazine, and suspended sediment. The explanatory variables provide easily measured quantities to serve as potential surrogate variables to estimate concentrations of the selected constituents through statistical regression. Statistical regression also facilitates accompanying estimates of uncertainty in the form of prediction intervals. Each regression model potentially can be used to estimate concentrations of a given constituent in real time. Among other regression diagnostics, the diagnostics used as indicators of general model reliability and reported herein include the adjusted R-squared, the residual standard error, residual plots, and p-values. Adjusted R-squared values for the Spring Creek models ranged from .582–.922 (dimensionless). The residual standard errors ranged from .073–.447 (base-10 logarithm). Adjusted R-squared values for the East Fork San Jacinto River models ranged from .253–.853 (dimensionless). The residual standard errors ranged from .076–.388 (base-10 logarithm). In conjunction with estimated concentrations, constituent loads can be estimated by multiplying the estimated concentration by the corresponding streamflow and by applying the appropriate conversion factor. The regression models presented in this report are site specific, that is, they are specific to the Spring Creek and East Fork San Jacinto River streamflow-gaging stations; however, the general methods that were developed and documented could be applied to most perennial streams for the purpose of estimating real-time water quality data.

Assessing the performance of remotely-sensed flooding indicators and their potential contribution to early warning for leptospirosis in Cambodia

PubMed Central

Ledien, Julia; Sorn, Sopheak; Hem, Sopheak; Huy, Rekol; Buchy, Philippe

2017-01-01

Remote sensing can contribute to early warning for diseases with environmental drivers, such as flooding for leptospirosis. In this study we assessed whether and which remotely-sensed flooding indicator could be used in Cambodia to study any disease for which flooding has already been identified as an important driver, using leptospirosis as a case study. The performance of six potential flooding indicators was assessed by ground truthing. The Modified Normalized Difference Water Index (MNDWI) was used to estimate the Risk Ratio (RR) of being infected by leptospirosis when exposed to floods it detected, in particular during the rainy season. Chi-square tests were also calculated. Another variable—the time elapsed since the first flooding of the year—was created using MNDWI values and was also included as explanatory variable in a generalized linear model (GLM) and in a boosted regression tree model (BRT) of leptospirosis infections, along with other explanatory variables. Interestingly, MNDWI thresholds for both detecting water and predicting the risk of leptospirosis seroconversion were independently evaluated at -0.3. Value of MNDWI greater than -0.3 was significantly related to leptospirosis infection (RR = 1.61 [1.10–1.52]; χ2 = 5.64, p-value = 0.02, especially during the rainy season (RR = 2.03 [1.25–3.28]; χ2 = 8.15, p-value = 0.004). Time since the first flooding of the year was a significant risk factor in our GLM model (p-value = 0.042). These results suggest that MNDWI may be useful as a risk indicator in an early warning remote sensing tool for flood-driven diseases like leptospirosis in South East Asia. PMID:28704461

Assessing the performance of remotely-sensed flooding indicators and their potential contribution to early warning for leptospirosis in Cambodia.

PubMed

Ledien, Julia; Sorn, Sopheak; Hem, Sopheak; Huy, Rekol; Buchy, Philippe; Tarantola, Arnaud; Cappelle, Julien

2017-01-01

Remote sensing can contribute to early warning for diseases with environmental drivers, such as flooding for leptospirosis. In this study we assessed whether and which remotely-sensed flooding indicator could be used in Cambodia to study any disease for which flooding has already been identified as an important driver, using leptospirosis as a case study. The performance of six potential flooding indicators was assessed by ground truthing. The Modified Normalized Difference Water Index (MNDWI) was used to estimate the Risk Ratio (RR) of being infected by leptospirosis when exposed to floods it detected, in particular during the rainy season. Chi-square tests were also calculated. Another variable-the time elapsed since the first flooding of the year-was created using MNDWI values and was also included as explanatory variable in a generalized linear model (GLM) and in a boosted regression tree model (BRT) of leptospirosis infections, along with other explanatory variables. Interestingly, MNDWI thresholds for both detecting water and predicting the risk of leptospirosis seroconversion were independently evaluated at -0.3. Value of MNDWI greater than -0.3 was significantly related to leptospirosis infection (RR = 1.61 [1.10-1.52]; χ2 = 5.64, p-value = 0.02, especially during the rainy season (RR = 2.03 [1.25-3.28]; χ2 = 8.15, p-value = 0.004). Time since the first flooding of the year was a significant risk factor in our GLM model (p-value = 0.042). These results suggest that MNDWI may be useful as a risk indicator in an early warning remote sensing tool for flood-driven diseases like leptospirosis in South East Asia.

Freshwater Vulnerability to Nitrate Contamination as an Indicator of Sustainability and Resilience within the Water-Energy-Food Nexus of the California Coastal Basins

NASA Astrophysics Data System (ADS)

Nanus, L.; Geyer, G.; Gurdak, J. J.; Orencio, P. M.; Endo, A.; Taniguchi, M.

2014-12-01

The California Coastal Basin (CCB) aquifers are representative of many coastal aquifers that are vulnerable to nonpoint-source (NPS) contamination from intense agriculture and increased urbanization combined with historical groundwater use and overdraft conditions. Overdraft has led to seawater intrusion along parts of the central California coast, which negatively affects food production because of high salinity concentrations in groundwater used for irrigation. Recent drought conditions in California have led to an increased need to further understand freshwater sustainability and resilience within the water-energy-food (WEF) nexus. Assessing the vulnerability of NPS contamination in groundwater provides valuable information for optimal resource management and policy. Vulnerability models of nitrate contamination in the CCB were developed as one of many indicators to evaluate risk in terms of susceptibility of the physical environment at local and regional scales. Multivariate logistic regression models were developed to predict the probability of NPS nitrate contamination in recently recharged groundwater and to identify significant explanatory variables as controlling factors in the CCB. Different factors were found to be significant in the sub-regions of the CCB and issues of scale are important. For example, land use is scale dependent because of the difference in land management practices between the CCB sub-regions. However, dissolved oxygen concentrations in groundwater, farm fertilizer, and soil thickness are scale invariant because they are significant both regionally and sub-regionally. Thus, the vulnerability models for the CCB show that different explanatory variables are scale invariant. This finding has important implications for accurately quantifying linkages between vulnerability and consequences within the WEF nexus, including inherent tradeoffs in water and food production in California and associated impacts on the local and regional economy, governance, environment, and society at multiple scales.

Unmodeled observation error induces bias when inferring patterns and dynamics of species occurrence via aural detections

USGS Publications Warehouse

McClintock, Brett T.; Bailey, Larissa L.; Pollock, Kenneth H.; Simons, Theodore R.

2010-01-01

The recent surge in the development and application of species occurrence models has been associated with an acknowledgment among ecologists that species are detected imperfectly due to observation error. Standard models now allow unbiased estimation of occupancy probability when false negative detections occur, but this is conditional on no false positive detections and sufficient incorporation of explanatory variables for the false negative detection process. These assumptions are likely reasonable in many circumstances, but there is mounting evidence that false positive errors and detection probability heterogeneity may be much more prevalent in studies relying on auditory cues for species detection (e.g., songbird or calling amphibian surveys). We used field survey data from a simulated calling anuran system of known occupancy state to investigate the biases induced by these errors in dynamic models of species occurrence. Despite the participation of expert observers in simplified field conditions, both false positive errors and site detection probability heterogeneity were extensive for most species in the survey. We found that even low levels of false positive errors, constituting as little as 1% of all detections, can cause severe overestimation of site occupancy, colonization, and local extinction probabilities. Further, unmodeled detection probability heterogeneity induced substantial underestimation of occupancy and overestimation of colonization and local extinction probabilities. Completely spurious relationships between species occurrence and explanatory variables were also found. Such misleading inferences would likely have deleterious implications for conservation and management programs. We contend that all forms of observation error, including false positive errors and heterogeneous detection probabilities, must be incorporated into the estimation framework to facilitate reliable inferences about occupancy and its associated vital rate parameters.

Ordinal probability effect measures for group comparisons in multinomial cumulative link models.

PubMed

Agresti, Alan; Kateri, Maria

2017-03-01

We consider simple ordinal model-based probability effect measures for comparing distributions of two groups, adjusted for explanatory variables. An "ordinal superiority" measure summarizes the probability that an observation from one distribution falls above an independent observation from the other distribution, adjusted for explanatory variables in a model. The measure applies directly to normal linear models and to a normal latent variable model for ordinal response variables. It equals Φ(β/2) for the corresponding ordinal model that applies a probit link function to cumulative multinomial probabilities, for standard normal cdf Φ and effect β that is the coefficient of the group indicator variable. For the more general latent variable model for ordinal responses that corresponds to a linear model with other possible error distributions and corresponding link functions for cumulative multinomial probabilities, the ordinal superiority measure equals exp(β)/[1+exp(β)] with the log-log link and equals approximately exp(β/2)/[1+exp(β/2)] with the logit link, where β is the group effect. Another ordinal superiority measure generalizes the difference of proportions from binary to ordinal responses. We also present related measures directly for ordinal models for the observed response that need not assume corresponding latent response models. We present confidence intervals for the measures and illustrate with an example. © 2016, The International Biometric Society.

Towards a neuro-computational account of prism adaptation.

PubMed

Petitet, Pierre; O'Reilly, Jill X; O'Shea, Jacinta

2017-12-14

Prism adaptation has a long history as an experimental paradigm used to investigate the functional and neural processes that underlie sensorimotor control. In the neuropsychology literature, prism adaptation behaviour is typically explained by reference to a traditional cognitive psychology framework that distinguishes putative functions, such as 'strategic control' versus 'spatial realignment'. This theoretical framework lacks conceptual clarity, quantitative precision and explanatory power. Here, we advocate for an alternative computational framework that offers several advantages: 1) an algorithmic explanatory account of the computations and operations that drive behaviour; 2) expressed in quantitative mathematical terms; 3) embedded within a principled theoretical framework (Bayesian decision theory, state-space modelling); 4) that offers a means to generate and test quantitative behavioural predictions. This computational framework offers a route towards mechanistic neurocognitive explanations of prism adaptation behaviour. Thus it constitutes a conceptual advance compared to the traditional theoretical framework. In this paper, we illustrate how Bayesian decision theory and state-space models offer principled explanations for a range of behavioural phenomena in the field of prism adaptation (e.g. visual capture, magnitude of visual versus proprioceptive realignment, spontaneous recovery and dynamics of adaptation memory). We argue that this explanatory framework can advance understanding of the functional and neural mechanisms that implement prism adaptation behaviour, by enabling quantitative tests of hypotheses that go beyond merely descriptive mapping claims that 'brain area X is (somehow) involved in psychological process Y'. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Asessing for Structural Understanding in Childrens' Combinatorial Problem Solving.

ERIC Educational Resources Information Center

English, Lyn

1999-01-01

Assesses children's structural understanding of combinatorial problems when presented in a variety of task situations. Provides an explanatory model of students' combinatorial understandings that informs teaching and assessment. Addresses several components of children's structural understanding of elementary combinatorial problems. (Contains 50…

ASSESSING ACCURACY OF NET CHANGE DERIVED FROM LAND COVER MAPS

EPA Science Inventory

Net change derived from land-cover maps provides important descriptive information for environmental monitoring and is often used as an input or explanatory variable in environmental models. The sampling design and analysis for assessing net change accuracy differ from traditio...

Complexity: A Frontier for Management Education

ERIC Educational Resources Information Center

Axley, Stephen R.; McMahon, Timothy R.

2006-01-01

This article critiques the mechanistic grounding of traditional management education and proposes complexity science as a fitting explanatory model for an age of complexity, contributing timely and important educational content and instructional processes to management education. It highlights some of those contributions and reviews instructional…

Pro-anorexia, weight-loss drugs and the internet: an "anti-recovery" explanatory model of anorexia.

PubMed

Fox, Nick; Ward, Katie; O'Rourke, Alan

2005-11-01

This paper explores the online "pro-anorexia" underground, a movement that supports those with anorexia and adopts an "anti-recovery" perspective on the disease. While encouraging a "healthy" diet to sustain an anorexic way-of-life, the movement also recommends the radical use of weight-loss pharmaceuticals to pursue and maintain low body weight, in contrast to their conventional use to treat obesity. Using ethnographic and interview data collected from participants in the "Anagrrl" website and online forum, we analyse the pro-anorexia (or "pro-ana") movement in terms of its underlying "explanatory model" of the disease, and contrast it with medical, psychosocial, sociocultural and feminist models that encourage a "normalisation" of body shape and weight. We suggest that for participants in pro-ana, anorexia represents stability and control, and Anagrrl offers support and guidance for those who wish to remain in this "sanctuary". We discuss the pro-anorexia movement's use of the internet to facilitate resistance to medical and social theories of disease, and its subversion of pharmaceutical technologies.

Independent Assessment Plan: LAV-25

DTIC Science & Technology

1989-06-27

Pages. Enter the total Block 7. Performing Organization Name(s) and number of pages. Address(es. Self -explanatory. Block 16. Price Code, Enter...organization Blocks 17. - 19. Security Classifications. performing the report. Self -explanatory. Enter U.S. Security Classification in accordance with U.S...Security Block 9. S oonsorina/Monitoring Acenc Regulations (i.e., UNCLASSIFIED). If form .Names(s) and Address(es). Self -explanatory. contains classified

Exploratory case study of students' main explanatory approaches to science concepts and their states of mental engagement

NASA Astrophysics Data System (ADS)

Nicdao-Quita, Maria Isabel T.

This study explored students' dominant ways of operating in science; the types of structuring that is evident, not in terms of ideas, but in terms of how the students think about, imagine, and relate to the physical processes. As the study progressed, the investigation of the students' ideas went beyond their prior knowledge; other significant dimensions emerged as these students interacted with the heating process. The students demonstrated rich and dynamic pictures of the heating process, and from these images, a larger picture of the mental entities and processes dominant in their understanding of the physical phenomenon. Four Filipino students studying in the United States were individually observed in their science classes, were visited at home, and were interviewed about water being heated. The analysis of each student's data led to the two constructs, the main explanatory approach and the students' states of mental engagement (SOME), while the student was cognitively and affectively connected with the phenomenon. The features of the main explanatory approach include an explanatory element and an affective element that pervade the students' thinking about the phenomenon. It is common to and dominant in students' thinking across time. It is the approach of the student taken as a holistic organization within the student when he or she starts dealing with the phenomenon. One of the assumptions behind dealing with the main explanatory approach is that it is much more connected with what kind of person the student is and with the state of mental engagement (SOME) the student is in. SOME refers to the personal energy of a student as he or she relates to and becomes involved with the physical process--there is absorption into the object of study. SOME is related to energizing the main explanatory approach. The interconnectedness of these two constructs can be viewed as a different level of abstraction or interpretation of the students' ways of thinking about the physical process. This way of looking at students' understanding and its connection with students' states of mental engagement has opened up an area with many possibilities, one of which is how the affective structures play a significant role in the exploration of science concepts.

Cognitive Modeling for Agent-Based Simulation of Child Maltreatment

NASA Astrophysics Data System (ADS)

Hu, Xiaolin; Puddy, Richard

This paper extends previous work to develop cognitive modeling for agent-based simulation of child maltreatment (CM). The developed model is inspired from parental efficacy, parenting stress, and the theory of planned behavior. It provides an explanatory, process-oriented model of CM and incorporates causality relationship and feedback loops from different factors in the social ecology in order for simulating the dynamics of CM. We describe the model and present simulation results to demonstrate the features of this model.

Management and Outcomes Following Surgery for Gastrointestinal Typhoid: An International, Prospective, Multicentre Cohort Study.

PubMed

2018-05-03

Gastrointestinal perforation is the most serious complication of typhoid fever, with a high disease burden in low-income countries. Reliable, prospective, contemporary surgical outcome data are scarce in these settings. This study aimed to investigate surgical outcomes following surgery for intestinal typhoid. Two multicentre, international prospective cohort studies of consecutive patients undergoing surgery for gastrointestinal typhoid perforation were conducted. Outcomes were measured at 30 days and included mortality, surgical site infection, organ space infection and reintervention rate. Multilevel logistic regression models were used to adjust for clinically plausible explanatory variables. Effect estimates are expressed as odds ratios (ORs) alongside their corresponding 95% confidence intervals. A total of 88 patients across the GlobalSurg 1 and GlobalSurg 2 studies were included, from 11 countries. Children comprised 38.6% (34/88) of included patients. Most patients (87/88) had intestinal perforation. The 30-day mortality rate was 9.1% (8/88), which was higher in children (14.7 vs. 5.6%). Surgical site infection was common, at 67.0% (59/88). Organ site infection was common, with 10.2% of patients affected. An ASA grade of III and above was a strong predictor of 30-day post-operative mortality, at the univariable level and following adjustment for explanatory variables (OR 15.82, 95% CI 1.53-163.57, p = 0.021). With high mortality and complication rates, outcomes from surgery for intestinal typhoid remain poor. Future studies in this area should focus on sustainable interventions which can reduce perioperative morbidity. At a policy level, improving these outcomes will require both surgical and public health system advances.

Culture, cultural factors and psychiatric diagnosis: review and projections.

PubMed

Alarcón, Renato D

2009-10-01

This paper aims to provide conceptual justifications for the inclusion of culture and cultural factors in psychiatric diagnosis, and logistic suggestions as to the content and use of this approach. A discussion of the scope and limitations of current diagnostic practice, criticisms from different quarters, and the role and relevance of culture in the diagnostic encounter, precede the examination of advantages and disadvantages of the approach. The cultural content of psychiatric diagnosis should include the main, well-recognized cultural variables, adequate family data, explanatory models, and strengths and weaknesses of every individual patient. The practical aspects include the acceptance of "cultural discordances" as a component of an updated definition of mental disorder, and the use of a refurbished cultural formulation. Clinical "telescoping" strategies to obtain relevant cultural data during the diagnostic interview, and areas of future research (including field trials on the cultural formulation and on "culture bound syndromes"), are outlined.

Buying a Better Air Force

DTIC Science & Technology

2006-03-01

identify if an explanatory variable may have been omitted due to model misspecification ( Ramsey , 1979). The RESET test resulted in failure to...Prob > F 0.0094 This model was also regressed using Huber-White estimators. Again, the Ramsey RESET test was done to ensure relevant...Aircraft. Annapolis, MD: Naval Institute Press, 2004. Ramsey , J. B. “ Tests for Specification Errors in Classical Least-Squares Regression Analysis

The Influence of Self-Efficacy and Motivational Factors on Academic Performance in General Chemistry Course: A Modeling Study

ERIC Educational Resources Information Center

Alci, Bulent

2015-01-01

This study aims to determine the predictive and explanatory model in terms of university students' academic performance in "General Chemistry" course and their motivational features. The participants were 169 university students in the 1st grade at university. Of the participants, 132 were female and 37 were male students. Regarding…

Developing a Model and Applications for Probabilities of Student Success: A Case Study of Predictive Analytics

ERIC Educational Resources Information Center

Calvert, Carol Elaine

2014-01-01

This case study relates to distance learning students on open access courses. It demonstrates the use of predictive analytics to generate a model of the probabilities of success and retention at different points, or milestones, in a student journey. A core set of explanatory variables has been established and their varying relative importance at…

Why Is Childhood Maltreatment Associated with Adolescent Substance Abuse? A Critical Review of Explanatory Models

ERIC Educational Resources Information Center

Hovdestad, Wendy E.; Tonmyr, Lil; Wekerle, Christine; Thornton, Tiffany

2011-01-01

Childhood maltreatment and adolescent substance abuse are important health issues that have been linked by research and theory for at least 50 years. Considering the intricacies of child maltreatment research, this paper aims to answer the question: which models show the most promise to explain why child maltreatment is a risk indicator for…

What Does It Mean to Be Pragmatic? Pragmatic Methods, Measures, and Models to Facilitate Research Translation

ERIC Educational Resources Information Center

Glasgow, Russell E.

2013-01-01

Background: One of the reasons for the slow and uncertain translation of research into practice is likely due to the emphasis in science on explanatory models and efficacy designs rather than more pragmatic approaches. Methods: Following a brief definition of what constitutes a pragmatic approach, I provide examples of pragmatic methods, measures,…

The Impact of Student Teaching Experience on Pre-Service Teachers' Readiness for Technology Integration: A Mixed Methods Study with Growth Curve Modeling

ERIC Educational Resources Information Center

Sun, Yan; Strobel, Johannes; Newby, Timothy J.

2017-01-01

Adopting a two-phase explanatory sequential mixed methods research design, the current study examined the impact of student teaching experiences on pre-service teachers' readiness for technology integration. In phase-1 of quantitative investigation, 2-level growth curve models were fitted using online repeated measures survey data collected from…

Fuel load modeling from mensuration attributes in temperate forests in northern Mexico

Treesearch

Maricela Morales-Soto; Marín Pompa-Garcia

2013-01-01

The study of fuels is an important factor in defining the vulnerability of ecosystems to forest fires. The aim of this study was to model a dead fuel load based on forest mensuration attributes from forest management inventories. A scatter plot analysis was performed and, from explanatory trends between the variables considered, correlation analysis was carried out...

The Four-Three-Four Model: Drawing on Partitioning, Equivalence, and Unit-Forming in a Quotient Sub-Construct Fraction Task

ERIC Educational Resources Information Center

Mitchell, Annie

2012-01-01

This paper demonstrates the explanatory power of Kieren's framework for rational number knowing (1988, 1992, 1993, 1995), renamed here the four-three-four model, by describing the different approaches of Grade 6 students to a quotient context task (sharing three or seven custard tarts between five people) using Kieren's terminology of…

Using a Market Ratio Factor in Faculty Salary Equity Studies. Professional File Number 103, Spring 2007

ERIC Educational Resources Information Center

Luna, Andrew L.

2007-01-01

This study used two multiple regression analyses to develop an explanatory model to determine which model might best explain faculty salaries. The central purpose of the study was to determine if using a single market ratio variable was a stronger predictor for faculty salaries than the use of dummy variables representing various disciplines.…

Fraying connections of caring women: an exemplar of including difference in the development of explanatory frameworks.

PubMed

Wuest, J

1997-01-01

While research exploring diverse groups enhances understanding of their unique perspectives and experiences, it also contributes to the exclusion of such groups from mainstream frameworks and solutions. The feminist grounded theory method allows for inclusion of marginalized groups through theoretical sensitivity to feminist theory and theoretical sampling. This paper demonstrates how this approach results in an explanatory framework that accounts for diverse realities in a study of women's caring. Fraying connections were identified as women's initial response to competing and changing caring demands. The range of dimensions and properties of fraying connections was identified through theoretical sampling guided by the emerging themes and theoretical sensitivity to issues of gender, culture, age, ability, class, and sexual orientation.

The Source of Tok Pisin Structures.

ERIC Educational Resources Information Center

Goulden, Rick J.

1989-01-01

The source of the similarities and differences produced by pidginization is a central question studied in Pidgin-Creole linguistics. Several explanatory approaches are discussed that have guided research in this area, including simplification, substratum, independent innovation, and universals. (27 references) (Author/OD)

Meeting the Challenge: Creating Engaging and Powerful Contexts for Literacy Learning

ERIC Educational Resources Information Center

Wilhelm, Jeffrey D.

2007-01-01

This article explores the conditions of "flow" experience from two studies into the literate lives of young men (Smith and Wilhelm 2002; 2006) that were explanatory, when present, of motivation and engagement in various activities including literacy, and when absent, of a lack of motivation and engagement in various activities including literacy.…

Research in Action II National Conference Proceedings (Lubbock, Texas, February 9-11, 1983). Volume II.

ERIC Educational Resources Information Center

Tucker, Jamie, Ed.

This conference program includes explanatory material and reprints 15 of the 43 papers presented in conference sessions. In addition to Rheta De Vries' keynote address--"Can Research Help Teachers Teach?"--research reports are published from four interest session tracks. Papers from the health/handicap track include Patricia Hutinger's…

Examination of the Relation between TEOG Score of Turkish Revolution History and Kemalism Course and Reading Comprehension Skill (An Example of Explanatory Sequential Mixed Design)

ERIC Educational Resources Information Center

Yuvaci, Ibrahim; Demir, Selçuk Besir

2016-01-01

This paper is aimed to determine the relation between reading comprehension skill and TEOG success. In this research, a mixed research method, sequential explanatory mixed design, is utilized to examine the relation between reading comprehension skills and TEOG success of 8th grade students throughly. In explanatory sequential mixed design…

Comparison of stream invertebrate response models for bioassessment metric

USGS Publications Warehouse

Waite, Ian R.; Kennen, Jonathan G.; May, Jason T.; Brown, Larry R.; Cuffney, Thomas F.; Jones, Kimberly A.; Orlando, James L.

2012-01-01

We aggregated invertebrate data from various sources to assemble data for modeling in two ecoregions in Oregon and one in California. Our goal was to compare the performance of models developed using multiple linear regression (MLR) techniques with models developed using three relatively new techniques: classification and regression trees (CART), random forest (RF), and boosted regression trees (BRT). We used tolerance of taxa based on richness (RICHTOL) and ratio of observed to expected taxa (O/E) as response variables and land use/land cover as explanatory variables. Responses were generally linear; therefore, there was little improvement to the MLR models when compared to models using CART and RF. In general, the four modeling techniques (MLR, CART, RF, and BRT) consistently selected the same primary explanatory variables for each region. However, results from the BRT models showed significant improvement over the MLR models for each region; increases in R2 from 0.09 to 0.20. The O/E metric that was derived from models specifically calibrated for Oregon consistently had lower R2 values than RICHTOL for the two regions tested. Modeled O/E R2 values were between 0.06 and 0.10 lower for each of the four modeling methods applied in the Willamette Valley and were between 0.19 and 0.36 points lower for the Blue Mountains. As a result, BRT models may indeed represent a good alternative to MLR for modeling species distribution relative to environmental variables.

Time-Frequency Analysis of Beach Bacteria Variations and its Implication for Recreational Water Quality Modeling

EPA Science Inventory

This paper explores the potential of time-frequency wavelet analysis in resolving beach bacteria concentration and possible explanatory variables across multiple time scales with temporal information still preserved. The wavelet scalograms of E. coli concentrations and the explan...

Characterizing Resilience and Growth Among Soldiers: A Trajectory Study

DTIC Science & Technology

2012-04-01

casualties of cruel environments or bad genetics . Positive psychology challenges the assumptions of the disease model. It calls for as much focus on...by psychologists, under several different rubrics : dispositional optimism by Carver and Scheier (1981), hope by Snyder (2000), and explanatory style

Long-term change in a behavioural trait: truncated spawning distribution and demography in Northeast Arctic cod.

PubMed

Opdal, Anders Frugård; Jørgensen, Christian

2015-04-01

Harvesting may be a potent driver of demographic change and contemporary evolution, which both may have great impacts on animal populations. Research has focused on changes in phenotypic traits that are easily quantifiable and for which time series exist, such as size, age, sex, or gonad size, whereas potential changes in behavioural traits have been under-studied. Here, we analyse potential drivers of long-term changes in a behavioural trait for the Northeast Arctic stock of Atlantic cod Gadus morhua, namely choice of spawning location. For 104 years (1866-1969), commercial catches were recorded annually and reported by county along the Norwegian coast. During this time period, spawning ground distribution has fluctuated with a trend towards more northerly spawning. Spawning location is analysed against a suite of explanatory factors including climate, fishing pressure, density dependence, and demography. We find that demography (age or age at maturation) had the highest explanatory power for variation in spawning location, while climate had a limited effect below statistical significance. As to potential mechanisms, some effects of climate may act through demography, and explanatory variables for demography may also have absorbed direct evolutionary change in migration distance for which proxies were unavailable. Despite these caveats, we argue that fishing mortality, either through demographic or evolutionary change, has served as an effective driver for changing spawning locations in cod, and that additional explanatory factors related to climate add no significant information. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

[Different explanatory models for addictive behavior in Turkish and German youths in Germany: significance for prevention and treatment].

PubMed

Penka, S; Krieg, S; Hunner, Ch; Heinz, A

2003-07-01

Due to cultural and social barriers, immigrants seldom frequent centers for information, counseling, and treatment of addictive disorders. We examine cultural differences in the explanatory models of addictive behavior among Turkish and German youths in Germany with statistical devices that map the concepts associated with problems of addiction. Relevant differences were found between the disorder concepts of Turkish and German youth. German but not Turkish youths classified eating disorders among severe addictive disorders and associated them with embarrassment and shame. Concerning substance abuse, German but not Turkish youths clearly differentiated between illegal drug abuse and the abuse of alcohol and nicotine. Nearly half of all Turkish youths rejected central medical concepts such as "physical dependence" or "reduced control of substance intake" as completely inadequate to characterize problems of addictive behavior. Preventive information programs must consider these differences and use concepts that are accepted and clearly associated with addictive behavior by immigrant populations.

Incomes, Attitudes, and Occurrences of Invasive Species: An Application to Signal Crayfish in Sweden

NASA Astrophysics Data System (ADS)

Gren, Ing-Marie; Campos, Monica; Edsman, Lennart; Bohman, Patrik

2009-02-01

This article analyzes and carries out an econometric test of the explanatory power of economic and attitude variables for occurrences of the nonnative signal crayfish in Swedish waters. Signal crayfish are a carrier of plague which threatens the native noble crayfish with extinction. Crayfish are associated with recreational and cultural traditions in Sweden, which may run against environmental preferences for preserving native species. Econometric analysis is carried out using panel data at the municipality level with economic factors and attitudes as explanatory variables, which are derived from a simple dynamic harvesting model. A log-normal model is used for the regression analysis, and the results indicate significant impacts on occurrences of waters with signal crayfish of changes in both economic and attitude variables. Variables reflecting environmental and recreational preferences have unexpected signs, where the former variable has a positive and the latter a negative impact on occurrences of waters with signal crayfish. These effects are, however, counteracted by their respective interaction effect with income.

Parents' explanatory models and hopes for outcomes of occupational therapy using a sensory integration approach.

PubMed

Cohn, Ellen S; Kramer, Jessica; Schub, Jamie A; May-Benson, Teresa

2014-01-01

PURPOSE. To describe parents' concerns and hopes for their children who would be receiving occupational therapy using a sensory integration approach. METHOD. Content analysis of 275 parental responses to three open-ended questions on developmental-sensory history intake forms. FINDINGS. Parents' descriptions of why they sought for their children were categorized into four overarching concerns about their children's challenges: self-regulation, interacting with peers, participating in skilled motor activities, and self-confidence. Parents often linked these concerns together, revealing explanatory models of how they make sense of potential relationships among their children's challenges and how these challenges affect occupational performance. Parents hoped occupational therapy would help their children develop self-understanding and frustration tolerance to self-regulate their behavior in socially acceptable ways. IMPLICATIONS. Assessment and intervention should explicitly focus on links among self-regulation, social participation, skills, and perceived competence to address parents' expectations. Copyright © 2014 by the American Occupational Therapy Association, Inc.

The Unified Lunar Control Network 2005

USGS Publications Warehouse

Archinal, Brent A.; Rosiek, Mark R.; Kirk, Randolph L.; Redding, Bonnie L.

2006-01-01

This report documents a new general unified lunar control network and lunar topographic model based on a combination of Clementine images and a previous network derived from Earth-based & Apollo photographs, and Mariner 10, & Galileo images. This photogrammetric network solution is the largest planetary control network ever completed. It includes the determination of the 3-D positions of 272,931 points on the lunar surface and the correction of the camera angles for 43,866 Clementine images, using 546,126 tie point measurements. The solution RMS is 20 ?m (= 0.9 pixels) in the image plane, with the largest residual of 6.4 pixels. The explanation given here, along with the accompanying files, comprises the release of the network information and of global lunar digital elevation models (DEMs) derived from the network. A paper that will describe the solution and network in further detail will be submitted to a refereed journal, and will include additional background information, solution details, discussion of accuracy and precision, and explanatory figures.

Tourette Syndrome and Tic Disorders

PubMed Central

Leckman, James F.

2005-01-01

Objective: This is a practical review of Tourette syndrome, including phenomenology, natural history, and state-of-the-art assessment and treatment. Method: Computerized literature searches were conducted under the keywords Tourette syndrome,tics, and children-adolescents. Results: Studies have documented the natural history of Tourette syndrome and its frequent co-occurrence with attention problems, obsessive-compulsive disorder (OCD), and a range of other mood and anxiety disorders, which are often of primary concern to patients and their families. Proper diagnosis and education are often very helpful for patients, parents, siblings, teachers, and peers. When necessary, available anti-tic treatments have proven efficacious. First-line options include the alpha adrenergic agents and the atypical neuroleptics, as well as behavioral interventions such as habit reversal. Conclusions: The study of tics and Tourette symdrome has led to the development of several pathophysiological models and helped in the development of management options. However, fully explanatory models are still needed that would allow for accurate prognostication in the course of illness and the development of improved treatments. PMID:21152158

Factors of interpersonal communication and behavioral health on medication self-efficacy and medication adherence.

PubMed

Archiopoli, Ashley; Ginossar, Tamar; Wilcox, Bryan; Avila, Magdalena; Hill, Ricky; Oetzel, John

2016-12-01

Despite devastating effects on health outcomes and disease progression, many people living with HIV (PLWH) are non-adherent to their medications. Medication self-efficacy is a pivotal factor in medication adherence, yet its formation and relationship with other factors are understudied. This study examines a model that considers the role of three communicative factors (patient-provider communication, social support, and social undermining) and two behavioral health factors (depression and alcohol abuse) and medication self-efficacy impacting medication adherence. Methods included a cross-sectional design using a survey questionnaire of 344 PLWH. Findings indicated that 25% of variance in medication adherence can be explained by a mediation model where depression (B = -.18) and provider-patient communication (B = .21) affect medication self-efficacy, which in turn impacts medication adherence (B = .64). Other variables, including demographics, did not add any explanatory power. These findings demonstrate the complex nature of medication adherence and the formation of medication self-efficacy.

Multimodality: a basis for augmentative and alternative communication--psycholinguistic, cognitive, and clinical/educational aspects.

PubMed

Loncke, Filip T; Campbell, Jamie; England, Amanda M; Haley, Tanya

2006-02-15

Message generating is a complex process involving a number of processes, including the selection of modes to use. When expressing a message, human communicators typically use a combination of modes. This phenomenon is often termed multimodality. This article explores the use of models that explain multimodality as an explanatory framework for augmentative and alternative communication (AAC). Multimodality is analysed from a communication, psycholinguistic, and cognitive perspective. Theoretical and applied topics within AAC can be explained or described within the multimodality framework considering iconicity, simultaneous communication, lexical organization, and compatibility of communication modes. Consideration of multimodality is critical to understanding underlying processes in individuals who use AAC and individuals who interact with them.

Explanatory style, dispositional optimism, and reported parental behavior.

PubMed

Hjelle, L A; Busch, E A; Warren, J E

1996-12-01

The relationship between two cognitive personality constructs (explanatory style and dispositional optimism) and retrospective self-reports of maternal and paternal behavior were investigated. College students (62 men and 145 women) completed the Life Orientation Test, Attributional Style Questionnaire, and Parental Acceptance-Rejection Questionnaire in a single session. As predicted, dispositional optimism was positively correlated with reported maternal and paternal warmth/acceptance and negatively correlated with aggression/hostility, neglect/indifference, and undifferentiated rejection during middle childhood. Unexpectedly, explanatory style was found to be more strongly associated with retrospective reports of paternal as opposed to maternal behavior. The implications of these results for future research concerning the developmental antecedents of differences in explanatory style and dispositional optimism are discussed.

Reproductive practices by patterns of marriage among Iranian women: study protocol for an explanatory sequential mixed methods design.

PubMed

Taghizadeh, Ziba; Vedadhir, Abouali; Behmanesh, Fereshteh; Ebadi, Abbas; Pourreza, Abulghasem; Abbasi-Shavazi, Mohammad Jalal

2015-09-18

Nowadays, nearly half of the world population lives in societies with low fertility or the below-replacement fertility. This potentially grounds the critical situation of reduction in the workforce and causes the aging of population due to an overall increase in life expectancy and standard of living. Hence, population and its transitions including the issue of fertility decline has become a topic of intense debate in the agenda-setting and policy-making processes in both the developed and developing countries. In this view, what can practically be done to respond to the fertility decline that entails effectively addressing the determinants of fertility change? In line with the literature, how people form their marriages or patterns of marriage is amongst influencing factors which potentially affect their reproductive practices as diverse societies recognize different conventions for marriage. This study is to examine women's reproductive practices by the various patterns of marriage using the explanatory sequential mixed methods design. This study has an explanatory sequential mixed methods design, the follow-up explanations variant model, with two strands. This design will be implemented in two distinct phases. In the first phase, a cross-sectional quantitative study will be done using a cluster sampling strategy on 850 married women 15-49 years old living in Babol city, Iran. In order to obtain a deeper understanding of the results of the quantitative phase, researchers will implement a qualitative research in the second phase of this study. This design will provide an explanation of the quantitative research results using the qualitative evidence. As patterns of marriage have implications for the status of women, their health and fertility, the result of this study can provide a rich source of information for the required health-related interventions and policies are required to put the demographic changes on the right track at micro and macro level and improve the reproductive practices of women at micro level.

Factors influencing subjects' comprehension of a set of medicine package inserts.

PubMed

Pires, Carla; Vigário, Marina; Cavaco, Afonso

2016-08-01

Background Package inserts (PIs) should promote the safe and effective use of medicines. The comprehension of PIs is related to socio-demographic features, such as education. Objectives To evaluate the participants' comprehension of a sample of PIs and to build an explanatory model of subjects' understanding of the content of these documents. Setting The data were collected from municipalities, city halls, firefighters, the military, schools and charities from two Portuguese regions. Methods Cross-sectional descriptive survey: 503 participants, homogeneously distributed by education and gender. The self-administered tool comprised questions on socio-demographic data, literacy tasks and comprehension evaluation of 12 purposively selected PIs. A logistic regression analysis was used. Main outcome measures Scores of numeracy tasks and comprehension. Results The average comprehension score for the PIs was 63 % (±32 %), with 48 % (n = 239) of the participants scoring <75 %. The most important predictors in explaining a comprehension score ≥75 % were having >12 years of education and correctly performing a numeracy task [respectively, OR 49.6 (CI 95 %: 22.8-108) and OR 2.48 (CI 95 %: 1.5-4.2)]. Conclusion An explanatory model of subjects' knowledge about the content of the tested PIs was built. Given that a high level of education and literacy were found to be the most relevant predictors for acceptable comprehension rates, PIs should be clearly written to assure that they are understood by all potential users, including the less educated. The evaluated PIs may thus need to be simplified.

Electric utility franchise guide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

Through franchise agreements, municipalities grant energy providers the use of public easements for the transmission of electricity and natural gas from power sources to consumers. Generally, access to the public rights-of-way is generated in exchange for the payment to the City of a percentage of the gross revenues of the utility. This Guide presents a Model Electric Utility Franchise Agreement, structured by the city of Houston, to address cost-saving and revenue-enhancing issues that should be considered by any municipality in both the day-to-day administration of existing franchises, and at the time of franchise renewal and renegotiation. In addition to themore » model agreement this Guide includes Explanatory Comments that provide the basis and rationale for certain sections of the agreement as well as a Summary of Major Elements of franchise agreements in over sixty US municipalities.« less

Impact of multicollinearity on small sample hydrologic regression models

NASA Astrophysics Data System (ADS)

Kroll, Charles N.; Song, Peter

2013-06-01

Often hydrologic regression models are developed with ordinary least squares (OLS) procedures. The use of OLS with highly correlated explanatory variables produces multicollinearity, which creates highly sensitive parameter estimators with inflated variances and improper model selection. It is not clear how to best address multicollinearity in hydrologic regression models. Here a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS). The performance of these four techniques was observed for varying sample sizes, correlation coefficients between the explanatory variables, and model error variances consistent with hydrologic regional regression models. The negative effects of multicollinearity are magnified at smaller sample sizes, higher correlations between the variables, and larger model error variances (smaller R2). The Monte Carlo simulation indicates that if the true model is known, multicollinearity is present, and the estimation and statistical testing of regression parameters are of interest, then PCR or PLS should be employed. If the model is unknown, or if the interest is solely on model predictions, is it recommended that OLS be employed since using more complicated techniques did not produce any improvement in model performance. A leave-one-out cross-validation case study was also performed using low-streamflow data sets from the eastern United States. Results indicate that OLS with stepwise selection generally produces models across study regions with varying levels of multicollinearity that are as good as biased regression techniques such as PCR and PLS.

Use of MODIS Vegetation Data in Dynamic SPARROW Modeling of Reactive Nitrogen Flux

NASA Astrophysics Data System (ADS)

Smith, R. A.; Brakebill, J.; Schwarz, G. E.; Nolin, A. W.; Shih, J.; Blomquist, J.; Alexander, R. B.; Macauley, M.

2012-12-01

SPARROW models are widely used to identify and quantify the sources of contaminants in watersheds and to predict their flux and concentration at specified locations downstream. Conventional SPARROW models are steady-state in form, and describe the average relationship between sources and stream conditions based on non-linear regression of long-term water quality monitoring data on spatially-referenced explanatory information. But many watershed management issues involve intra- and inter-annual changes in contaminant sources, hydrologic forcing, or other environmental conditions which cause a temporary imbalance between watershed inputs and outputs. Dynamic behavior of the system relating to changes in watershed storage and processing then becomes important. We describe the results of dynamic statistical calibration of a SPARROW model of total reactive nitrogen flux in the Potomac River Basin based on seasonal water quality and watershed explanatory data for 80 monitoring stations over the period 2000 to 2008. One challenge in dynamic modeling of reactive nitrogen is obtaining frequently-reported, spatially-detailed input data on the phenology of agricultural production and growth of other terrestrial vegetation. In this NASA-funded research, we use the Enhanced Vegetation Index (EVI) and gross primary productivity (GPP) data from the Terra Satellite-borne MODIS sensor to parameterize seasonal uptake and release of nitrogen. The spatial reference frame of the model is a 16,000-reach, 1:100,000-scale stream network, and the computational time step is seasonal. Precipitation and temperature data are from PRISM. The model describes transient storage and transport of nitrogen from multiple nonpoint sources including fertilized cropland, pasture, urban/suburban land, and atmospheric deposition. Removal of nitrogen from watershed storage to stream channels and to "permanent" sinks (deep groundwater and the atmosphere) occurs as parallel first-order processes. Point sources of nitrogen bypass storage and flow directly to stream channels. Model results indicate that, on average, a little more than half of the reactive nitrogen flux comes from transient storage; but in some sub-watersheds a large majority of the flux comes from stored nitrogen input to the watershed in previous seasons and years.

Spatial Modeling of Flood Duration in Amazonian Floodplains Through Radar Remote Sensing and Generalized Linear Models

NASA Astrophysics Data System (ADS)

Ferreira-Ferreira, J.; Francisco, M. S.; Silva, T. S. F.

2017-12-01

Amazon floodplains play an important role in biodiversity maintenance and provide important ecosystem services. Flood duration is the prime factor modulating biogeochemical cycling in Amazonian floodplain systems, as well as influencing ecosystem structure and function. However, due to the absence of accurate terrain information, fine-scale hydrological modeling is still not possible for most of the Amazon floodplains, and little is known regarding the spatio-temporal behavior of flooding in these environments. Our study presents an new approach for spatial modeling of flood duration, using Synthetic Aperture Radar (SAR) and Generalized Linear Modeling. Our focal study site was Mamirauá Sustainable Development Reserve, in the Central Amazon. We acquired a series of L-band ALOS-1/PALSAR Fine-Beam mosaics, chosen to capture the widest possible range of river stage heights at regular intervals. We then mapped flooded area on each image, and used the resulting binary maps as the response variable (flooded/non-flooded) for multiple logistic regression. Explanatory variables were accumulated precipitation 15 days prior and the water stage height recorded in the Mamirauá lake gauging station observed for each image acquisition date, Euclidean distance from the nearest drainage, and slope, terrain curvature, profile curvature, planform curvature and Height Above the Nearest Drainage (HAND) derived from the 30-m SRTM DEM. Model results were validated with water levels recorded by ten pressure transducers installed within the floodplains, from 2014 to 2016. The most accurate model included water stage height and HAND as explanatory variables, yielding a RMSE of ±38.73 days of flooding per year when compared to the ground validation sites. The largest disagreements were 57 days and 83 days for two validation sites, while remaining locations achieved absolute errors lower than 38 days. In five out of nine validation sites, the model predicted flood durations with disagreements lower than 20 days. The method extends our current capability to answer relevant scientific questions regarding floodplain ecological structure and functioning, and allows forecasting of ecological and biogeochemical alterations under climate change scenarios, using readily available datasets.

Predicting factors for malaria re-introduction: an applied model in an elimination setting to prevent malaria outbreaks.

PubMed

Ranjbar, Mansour; Shoghli, Alireza; Kolifarhood, Goodarz; Tabatabaei, Seyed Mehdi; Amlashi, Morteza; Mohammadi, Mahdi

2016-03-02

Malaria re-introduction is a challenge in elimination settings. To prevent re-introduction, receptivity, vulnerability, and health system capacity of foci should be monitored using appropriate tools. This study aimed to design an applicable model to monitor predicting factors of re-introduction of malaria in highly prone areas. This exploratory, descriptive study was conducted in a pre-elimination setting with a high-risk of malaria transmission re-introduction. By using nominal group technique and literature review, a list of predicting indicators for malaria re-introduction and outbreak was defined. Accordingly, a checklist was developed and completed in the field for foci affected by re-introduction and for cleared-up foci as a control group, for a period of 12 weeks before re-introduction and for the same period in the previous year. Using field data and analytic hierarchical process (AHP), each variable and its sub-categories were weighted, and by calculating geometric means for each sub-category, score of corresponding cells of interaction matrices, lower and upper threshold of different risks strata, including low and mild risk of re-introduction and moderate and high risk of malaria outbreaks, were determined. The developed predictive model was calibrated through resampling with different sets of explanatory variables using R software. Sensitivity and specificity of the model were calculated based on new samples. Twenty explanatory predictive variables of malaria re-introduction were identified and a predictive model was developed. Unpermitted immigrants from endemic neighbouring countries were determined as a pivotal factor (AHP score: 0.181). Moreover, quality of population movement (0.114), following malaria transmission season (0.088), average daily minimum temperature in the previous 8 weeks (0.062), an outdoor resting shelter for vectors (0.045), and rainfall (0.042) were determined. Positive and negative predictive values of the model were 81.8 and 100 %, respectively. This study introduced a new, simple, yet reliable model to forecast malaria re-introduction and outbreaks eight weeks in advance in pre-elimination and elimination settings. The model incorporates comprehensive deterministic factors that can easily be measured in the field, thereby facilitating preventive measures.

The roots of violence: converging psychoanalytic explanatory models for power struggles and violence in schools.

PubMed

Twemlow, S W

2000-10-01

This paper demonstrates that several psychoanalytic models taken together converge to collectively explain school violence and power struggles better than each does alone. Using my own experience in doing psychoanalytically informed community intervention, I approach the problem of school violence from a combination of Adlerian, Stollerian, dialectical social systems, and Klein-Bion perspectives. This integrated model is then applied to the Columbine High School massacre in Littleton, Colorado.

Theoretical Models for Aircraft Availability: Classical Approach to Identification of Trends, Seasonality, and System Constraints in the Development of Realized Models

DTIC Science & Technology

2004-03-01

predicting future events ( Heizer and Render , 1999). Forecasting techniques fall into two major categories, qualitative and quantitative methods...Globemaster III.” Excerpt from website. www.globalsecurity.org/military /systems/ aircraft/c-17-history.htm. 2003. Heizer , Jay, and Barry Render ...of the past data used to make the forecast ( Heizer , et. al., 1999). Explanatory forecasting models assume that the variable being forecasted

Longitudinal Course of Risk for Parental Post-Adoption Depression

PubMed Central

Foli, Karen J.; South, Susan C.; Lim, Eunjung; Hebdon, Megan

2016-01-01

Objective To determine whether the Postpartum Depression Predictors Inventory-Revised (PDPI-R) could be used to reveal distinct classes of adoptive parents across time. Design Longitudinal data were collected via online surveys at 4-6 weeks pre-placement, 4-6 weeks post-placement, and 5-6 months post-placement. Setting Participants were primarily clients of the largest adoption agency in the United States. Participants Participants included 127 adoptive parents (68 mothers and 59 fathers). Methods We applied a latent class growth analysis to the PDPI-R and conducted mixed effects modeling of class, time, and class×time interaction for the following categories of explanatory variables: parental expectations; interpersonal variables; psychological symptoms; and life orientation. Results Four latent trajectory classes were found. Class 1 (55% of sample) showed a stably low level of PDPI-R scores over time. Class 2 (32%) reported mean scores below the cut-off points at all three time points. Class 3 (8%) started at an intermediate level and increased after post-placement, but decreased at 5-6 months post-placement. Class 4 (5%) had high mean scores at all three time points. Significant main effects were found for almost all explanatory variables for class and for several variables for time. Significant interactions between class and time were found for expectations about the child and amount of love and ambivalence in parent's intimate relationship. Conclusion Findings may assist nurses to be alert to trajectories of risk for post-adoption depression. Additional factors, not included in the PDPI-R, to determine risk for post-adoption depression may be needed for adoptive parents. PMID:26874267

[The meanings of masculinity, sexuality, power and violence among adolescents].

PubMed

Villaseñor-Farías, Martha; Castañeda-Torres, Jorge D

2003-01-01

To analyze perceived meanings of masculinity and power related to sexual violence among adolescents. A qualitative study was carried out between 1998 and 2000 in the metropolitan area of Guadalajara, Mexico, among 155 junior high and high school male/female students. Information was collected from 12 focal groups in two-hour sessions. Data collection instruments included: interviews, observation, and instruction guides. Data were recorded using notes and tape recordings. Oral and written information was transcribed, categorized, and coded, in order to construct matrixes and interpret results. Symbolic explanatory concepts related with rape included: constructivism vs. naturalism, heteronomous moral posture, and early exchange towards respect and human rights. Females were perceived as the real and potential victims. Males were perceived as violent by nature or under challenge, and prone to be victimized only if they were children, unmanly, or homosexual. Analysis objects included motives, power, female refusal, accusation, consequences, management, and prevention. Sexual violence is symbolized within the realm of explanatory and moral controversy. The ideological values of masculinity legitimate both legal and judiciary impunity. Social meanings and adolescent participation should be considered in research and interventions.

Estimating and Modelling Bias of the Hierarchical Partitioning Public-Domain Software: Implications in Environmental Management and Conservation

PubMed Central

Olea, Pedro P.; Mateo-Tomás, Patricia; de Frutos, Ángel

2010-01-01

Background Hierarchical partitioning (HP) is an analytical method of multiple regression that identifies the most likely causal factors while alleviating multicollinearity problems. Its use is increasing in ecology and conservation by its usefulness for complementing multiple regression analysis. A public-domain software “hier.part package” has been developed for running HP in R software. Its authors highlight a “minor rounding error” for hierarchies constructed from >9 variables, however potential bias by using this module has not yet been examined. Knowing this bias is pivotal because, for example, the ranking obtained in HP is being used as a criterion for establishing priorities of conservation. Methodology/Principal Findings Using numerical simulations and two real examples, we assessed the robustness of this HP module in relation to the order the variables have in the analysis. Results indicated a considerable effect of the variable order on the amount of independent variance explained by predictors for models with >9 explanatory variables. For these models the nominal ranking of importance of the predictors changed with variable order, i.e. predictors declared important by its contribution in explaining the response variable frequently changed to be either most or less important with other variable orders. The probability of changing position of a variable was best explained by the difference in independent explanatory power between that variable and the previous one in the nominal ranking of importance. The lesser is this difference, the more likely is the change of position. Conclusions/Significance HP should be applied with caution when more than 9 explanatory variables are used to know ranking of covariate importance. The explained variance is not a useful parameter to use in models with more than 9 independent variables. The inconsistency in the results obtained by HP should be considered in future studies as well as in those already published. Some recommendations to improve the analysis with this HP module are given. PMID:20657734

Towards Greater Specificity in Identifying Associations Among Interparental Aggression, Child Emotional Reactivity to Conflict, and Child Problems

PubMed Central

Davies, Patrick T.; Cicchetti, Dante; Martin, Meredith J.

2012-01-01

This study examined specific forms of emotional reactivity to conflict and temperamental emotionality as explanatory mechanisms in pathways among interparental aggression and child psychological problems. Participants of the multi-method, longitudinal study included 201 two-year-old children and their mothers who had experienced elevated violence in the home. Consistent with emotional security theory, autoregressive structural equation model analyses indicated that children’s fearful reactivity to conflict was the only consistent mediator in the associations among interparental aggression and their internalizing and externalizing symptoms one year later. Pathways remained significant across maternal and observer ratings of children’s symptoms and with the inclusion of other predictors and mediators, including children’s sad and angry forms of reactivity to conflict, temperamental emotionality, gender, and socioeconomic status. PMID:22716918

An empirical comparison of statistical tests for assessing the proportional hazards assumption of Cox's model.

PubMed

Ng'andu, N H

1997-03-30

In the analysis of survival data using the Cox proportional hazard (PH) model, it is important to verify that the explanatory variables analysed satisfy the proportional hazard assumption of the model. This paper presents results of a simulation study that compares five test statistics to check the proportional hazard assumption of Cox's model. The test statistics were evaluated under proportional hazards and the following types of departures from the proportional hazard assumption: increasing relative hazards; decreasing relative hazards; crossing hazards; diverging hazards, and non-monotonic hazards. The test statistics compared include those based on partitioning of failure time and those that do not require partitioning of failure time. The simulation results demonstrate that the time-dependent covariate test, the weighted residuals score test and the linear correlation test have equally good power for detection of non-proportionality in the varieties of non-proportional hazards studied. Using illustrative data from the literature, these test statistics performed similarly.

The Traditional Model Does Not Explain Attitudes Toward Euthanasia: A Web-Based Survey of the General Public in Finland.

PubMed

Terkamo-Moisio, Anja; Kvist, Tarja; Laitila, Teuvo; Kangasniemi, Mari; Ryynänen, Olli-Pekka; Pietilä, Anna-Maija

2017-08-01

The debate about euthanasia is ongoing in several countries including Finland. However, there is a lack of information on current attitudes toward euthanasia among general Finnish public. The traditional model for predicting individuals' attitudes to euthanasia is based on their age, gender, educational level, and religiosity. However, a new evaluation of religiosity is needed due to the limited operationalization of this factor in previous studies. This study explores the connections between the factors of the traditional model and the attitudes toward euthanasia among the general public in the Finnish context. The Finnish public's attitudes toward euthanasia have become remarkably more positive over the last decade. Further research is needed on the factors that predict euthanasia attitudes. We suggest two different explanatory models for consideration: one that emphasizes the value of individual autonomy and another that approaches euthanasia from the perspective of fears of death or the process of dying.

On use of the multistage dose-response model for assessing laboratory animal carcinogenicity

PubMed Central

Nitcheva, Daniella; Piegorsch, Walter W.; West, R. Webster

2007-01-01

We explore how well a statistical multistage model describes dose-response patterns in laboratory animal carcinogenicity experiments from a large database of quantal response data. The data are collected from the U.S. EPA’s publicly available IRIS data warehouse and examined statistically to determine how often higher-order values in the multistage predictor yield significant improvements in explanatory power over lower-order values. Our results suggest that the addition of a second-order parameter to the model only improves the fit about 20% of the time, while adding even higher-order terms apparently does not contribute to the fit at all, at least with the study designs we captured in the IRIS database. Also included is an examination of statistical tests for assessing significance of higher-order terms in a multistage dose-response model. It is noted that bootstrap testing methodology appears to offer greater stability for performing the hypothesis tests than a more-common, but possibly unstable, “Wald” test. PMID:17490794

Multi-scale Mexican spotted owl (Strix occidentalis lucida) nest/roost habitat selection in Arizona and a comparison with single-scale modeling results

Treesearch

Brad C. Timm; Kevin McGarigal; Samuel A. Cushman; Joseph L. Ganey

2016-01-01

Efficacy of future habitat selection studies will benefit by taking a multi-scale approach. In addition to potentially providing increased explanatory power and predictive capacity, multi-scale habitat models enhance our understanding of the scales at which species respond to their environment, which is critical knowledge required to implement effective...

Non-Equilbrium Fermi Gases

DTIC Science & Technology

2016-02-02

understanding is the experimental verification of a new model of light-induced loss spectra, employing continuum-dressed basis states, which agrees in...and additional qualifiers separated by commas, e.g. Smith, Richard, J, Jr. 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES). Self -explanatory... verification of a new model of light-induced loss spectra, employing continuum-dressed basis states, which agrees in shape and magnitude with all of our

A database for propagation models

NASA Technical Reports Server (NTRS)

Kantak, Anil V.; Suwitra, Krisjani; Le, Chuong

1995-01-01

A database of various propagation phenomena models that can be used by telecommunications systems engineers to obtain parameter values for systems design is presented. This is an easy-to-use tool and is currently available for either a PC using Excel software under Windows environment or a Macintosh using Excel software for Macintosh. All the steps necessary to use the software are easy and many times self explanatory.

Modeling Alcohol Use Intensity among Students at a Historically Black University: The Role of Social Norms, Perceptions for Risk, and Selected Demographic Variables

ERIC Educational Resources Information Center

Lewis, Todd F.; Likis-Werle, Elizabeth; Fulton, Cheryl L.

2012-01-01

Drinking patterns and rates at historically Black colleges and universities (HBCU) are not well understood. Social norms and perceptions of risk are two explanatory mechanisms that have accounted for a significant amount of variance in college student drinking at predominantly White campuses. However, these models have not been examined among…

A comparison of the physical and anthropometric qualities explanatory of talent in the elite junior Australian football development pathway.

PubMed

Woods, Carl T; Cripps, Ashley; Hopper, Luke; Joyce, Christopher

2017-07-01

To compare the physical and anthropometric qualities explanatory of talent at two developmental levels in junior Australian football (AF). Cross-sectional observational. From a total of 134 juniors, two developmental levels were categorised; U16 (n=50; 15.6±0.3 y), U18 (n=84; 17.4±0.5 y). Within these levels, two groups were a priori defined; talent identified (U16; n=25; 15.7±0.2 y; U18 n=42; 17.5±0.4 y), non-talent identified (U16; n=25; 15.6±0.4 y; U18; n=42; 17.3±0.6 y). Players completed seven physical and anthropometric assessments commonly utilised for talent identification in AF. Binary logistic regression models were built to identify the qualities most explanatory of talent at each level. A combination of standing height, dominant leg dynamic vertical jump height and 20m sprint time provided the most parsimonious explanation of talent at the U16 level (AICc=60.05). At the U18 level, it was a combination of body mass and 20m sprint time that provided the most parsimonious explanation of talent (AICc=111.27). Despite similarities, there appears to be distinctive differences in physical and anthropometric qualities explanatory of talent at the U16 and U18 level. Coaches may view physical and anthropometric qualities more (or less) favourably at different levels of the AF developmental pathway. Given these results, future work should implement a longitudinal design, as physical and/or anthropometric qualities may deteriorate (or emerge) as junior AF players develop. Copyright © 2016 Sports Medicine Australia. All rights reserved.

Optimal population prediction of sandhill crane recruitment based on climate-mediated habitat limitations

USGS Publications Warehouse

Gerber, Brian D.; Kendall, William L.; Hooten, Mevin B.; Dubovsky, James A.; Drewien, Roderick C.

2015-01-01

Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (<1 year old) sandhill crane Grus canadensis recruitment of the Rocky Mountain Population (RMP). We consider spatial climate predictors motivated by hypotheses of how drought across multiple time-scales and spring/summer weather affects recruitment.Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression.Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring–summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect.Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond.Generalizable predictive models (trained by out-of-sample fit and based on ecological hypotheses) are needed by conservation and management decision-makers. Statistical regularization improves predictions and provides a general framework for fitting models with a large number of predictors, even those with collinearity, to simultaneously identify an optimal predictive model while conducting rigorous Bayesian model selection. Our framework is important for understanding population dynamics under a changing climate and has direct applications for making harvest and habitat management decisions.

Interdisciplinary and Cross-Cultural Perspectives on Explanatory Coexistence.

PubMed

Watson-Jones, Rachel E; Busch, Justin T A; Legare, Cristine H

2015-10-01

Natural and supernatural explanations are used to interpret the same events in a number of predictable and universal ways. Yet little is known about how variation in diverse cultural ecologies influences how people integrate natural and supernatural explanations. Here, we examine explanatory coexistence in three existentially arousing domains of human thought: illness, death, and human origins using qualitative data from interviews conducted in Tanna, Vanuatu. Vanuatu, a Melanesian archipelago, provides a cultural context ideal for examining variation in explanatory coexistence due to the lack of industrialization and the relatively recent introduction of Christianity and Western education. We argue for the integration of interdisciplinary methodologies from cognitive science and anthropology to inform research on explanatory coexistence. Copyright © 2015 Cognitive Science Society, Inc.

POLO2: a user's guide to multiple Probit Or LOgit analysis

Treesearch

Robert M. Russell; N. E. Savin; Jacqueline L. Robertson

1981-01-01

This guide provides instructions for the use of POLO2, a computer program for multivariate probit or logic analysis of quantal response data. As many as 3000 test subjects may be included in a single analysis. Including the constant term, up to nine explanatory variables may be used. Examples illustrating input, output, and uses of the program's special features...

The Law, the Student, and the Catholic School.

ERIC Educational Resources Information Center

Permuth, Steve; And Others

Providing explanatory information regarding the legal principles and issues affecting Catholic school educators, this handbook summarizes student rights, contractual arrangements, and state and federal requirements as they apply to parochial schools. The legal issues involved in torts of negligence, including establishment and violation of…

10 CFR 217.93 - Communications.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 10 Energy 3 2013-01-01 2013-01-01 false Communications. 217.93 Section 217.93 Energy DEPARTMENT OF ENERGY OIL ENERGY PRIORITIES AND ALLOCATIONS SYSTEM Miscellaneous Provisions § 217.93 Communications. All communications concerning this part, including requests for copies of the regulation and explanatory information...

Electric Motors: Technical Terminology Bulletin. Terminotech, Vol. 1, No. 2.

ERIC Educational Resources Information Center

General Electric Co. of Canada, Ltd., Montreal, Quebec.

This issue of a bulletin of technological terminology is devoted to electric motors. A brief narrative on the subject is included in both French and English. An English-French dictionary of terms comprises the bulk of the document. Explanatory illustrations are appended (JB).

Modification of selected South Carolina bridge-scour envelope curves

USGS Publications Warehouse

Benedict, Stephen T.; Caldwell, Andral W.

2012-01-01

Historic scour was investigated at 231 bridges in the Piedmont and Coastal Plain physiographic provinces of South Carolina by the U.S. Geological Survey in cooperation with the South Carolina Department of Transportation. These investigations led to the development of field-derived envelope curves that provided supplementary tools to assess the potential for scour at bridges in South Carolina for selected scour components that included clear-water abutment, contraction, and pier scour, and live-bed pier and contraction scour. The envelope curves consist of a single curve with one explanatory variable encompassing all of the measured field data for the respective scour components. In the current investigation, the clear-water abutment-scour and live-bed contraction-scour envelope curves were modified to include a family of curves that utilized two explanatory variables, providing a means to further refine the assessment of scour potential for those specific scour components. The modified envelope curves and guidance for their application are presented in this report.

The Association between Regional Environmental Factors and Road Trauma Rates: A Geospatial Analysis of 10 Years of Road Traffic Crashes in British Columbia, Canada

PubMed Central

Brubacher, Jeffrey R.; Chan, Herbert; Erdelyi, Shannon; Schuurman, Nadine; Amram, Ofer

2016-01-01

Background British Columbia, Canada is a geographically large jurisdiction with varied environmental and socio-cultural contexts. This cross-sectional study examined variation in motor vehicle crash rates across 100 police patrols to investigate the association of crashes with key explanatory factors. Methods Eleven crash outcomes (total crashes, injury crashes, fatal crashes, speed related fatal crashes, total fatalities, single-vehicle night-time crashes, rear-end collisions, and collisions involving heavy vehicles, pedestrians, cyclists, or motorcyclists) were identified from police collision reports and insurance claims and mapped to police patrols. Six potential explanatory factors (intensity of traffic law enforcement, speed limits, climate, remoteness, socio-economic factors, and alcohol consumption) were also mapped to police patrols. We then studied the association between crashes and explanatory factors using negative binomial models with crash count per patrol as the response variable and explanatory factors as covariates. Results Between 2003 and 2012 there were 1,434,239 insurance claim collisions, 386,326 police reported crashes, and 3,404 fatal crashes. Across police patrols, there was marked variation in per capita crash rate and in potential explanatory factors. Several factors were associated with crash rates. Percent roads with speed limits ≤ 60 km/hr was positively associated with total crashes, injury crashes, rear end collisions, and collisions involving pedestrians, cyclists, and heavy vehicles; and negatively associated with single vehicle night-time crashes, fatal crashes, fatal speeding crashes, and total fatalities. Higher winter temperature was associated with lower rates of overall collisions, single vehicle night-time collisions, collisions involving heavy vehicles, and total fatalities. Lower socio-economic status was associated with higher rates of injury collisions, pedestrian collisions, fatal speeding collisions, and fatal collisions. Regions with dedicated traffic officers had fewer fatal crashes and fewer fatal speed related crashes but more rear end crashes and more crashes involving cyclists or pedestrians. The number of traffic citations per 1000 drivers was positively associated with total crashes, fatal crashes, total fatalities, fatal speeding crashes, injury crashes, single vehicle night-time crashes, and heavy vehicle crashes. Possible explanations for these associations are discussed. Conclusions There is wide variation in per capita rates of motor vehicle crashes across BC police patrols. Some variation is explained by factors such as climate, road type, remoteness, socioeconomic variables, and enforcement intensity. The ability of explanatory factors to predict crash rates would be improved if considered with local traffic volume by all travel modes. PMID:27099930

Identifying the physical and anthropometric qualities explanatory of paddling adolescents.

PubMed

Sinclair, Wade H; Leicht, Anthony S; Eady, Troy W; Marshall, Nick J; Woods, Carl T

2017-12-01

This study aimed to identify the physical and/or anthropometric qualities explanatory of adolescent surf lifesavers participating in paddling activities. Cross-sectional observational study. A total of 53 (14-18years) male participants were recruited and classified into two groups; paddlers (n=30; actively participating in paddling), non-paddlers (n=23; not actively participating in paddling). All participants completed a testing battery that consisted of 16 physical (isometric strength and muscular endurance) and anthropometric (height, mass, segment lengths and breadths) assessments. Binary logistic regression models and receiver operating characteristic curves were built to identify the physical and/or anthropometric qualities most explanatory of paddling status (two levels: 1=paddlers, 0=non-paddlers). Significant between group differences were noted for 14 of the 16 assessments (P<0.05; d=0.59-1.29). However, it was the combination of horizontal shoulder abduction isometric strength, body mass, and sitting height that provided the greatest association with paddling status (Akaike Information Criterion=47.13). This full model successfully detected 87% and 70% of the paddlers and non-paddlers, respectively, with an area under the curve of 84.2%. These results indicate that there are distinctive physical and anthropometric qualities that may be advantageous for prospective paddling athletes to possess. Practitioners should integrate assessments of horizontal shoulder abduction isometric strength, body mass, and sitting height, as well as their subsequent cut-off thresholds, into talent detection programs focused toward the recognition of performance potential in paddling-oriented sports. Copyright © 2017 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

A digital spatial predictive model of land-use change using economic and environmental inputs and a statistical tree classification approach: Thailand, 1970s--1990s

NASA Astrophysics Data System (ADS)

Felkner, John Sames

The scale and extent of global land use change is massive, and has potentially powerful effects on the global climate and global atmospheric composition (Turner & Meyer, 1994). Because of this tremendous change and impact, there is an urgent need for quantitative, empirical models of land use change, especially predictive models with an ability to capture the trajectories of change (Agarwal, Green, Grove, Evans, & Schweik, 2000; Lambin et al., 1999). For this research, a spatial statistical predictive model of land use change was created and run in two provinces of Thailand. The model utilized an extensive spatial database, and used a classification tree approach for explanatory model creation and future land use (Breiman, Friedman, Olshen, & Stone, 1984). Eight input variables were used, and the trees were run on a dependent variable of land use change measured from 1979 to 1989 using classified satellite imagery. The derived tree models were used to create probability of change surfaces, and these were then used to create predicted land cover maps for 1999. These predicted 1999 maps were compared with actual 1999 landcover derived from 1999 Landsat 7 imagery. The primary research hypothesis was that an explanatory model using both economic and environmental input variables would better predict future land use change than would either a model using only economic variables or a model using only environmental. Thus, the eight input variables included four economic and four environmental variables. The results indicated a very slight superiority of the full models to predict future agricultural change and future deforestation, but a slight superiority of the economic models to predict future built change. However, the margins of superiority were too small to be statistically significant. The resulting tree structures were used, however, to derive a series of principles or "rules" governing land use change in both provinces. The model was able to predict future land use, given a series of assumptions, with 90 percent overall accuracies. The model can be used in other developing or developed country locations for future land use prediction, determination of future threatened areas, or to derive "rules" or principles driving land use change.

Nitrogen deposition outweighs climatic variability in driving annual growth rate of canopy beech trees: Evidence from long-term growth reconstruction across a geographic gradient.

PubMed

Gentilesca, Tiziana; Rita, Angelo; Brunetti, Michele; Giammarchi, Francesco; Leonardi, Stefano; Magnani, Federico; van Noije, Twan; Tonon, Giustino; Borghetti, Marco

2018-07-01

In this study, we investigated the role of climatic variability and atmospheric nitrogen deposition in driving long-term tree growth in canopy beech trees along a geographic gradient in the montane belt of the Italian peninsula, from the Alps to the southern Apennines. We sampled dominant trees at different developmental stages (from young to mature tree cohorts, with tree ages spanning from 35 to 160 years) and used stem analysis to infer historic reconstruction of tree volume and dominant height. Annual growth volume (G V ) and height (G H ) variability were related to annual variability in model simulated atmospheric nitrogen deposition and site-specific climatic variables, (i.e. mean annual temperature, total annual precipitation, mean growing period temperature, total growing period precipitation, and standard precipitation evapotranspiration index) and atmospheric CO 2 concentration, including tree cambial age among growth predictors. Generalized additive models (GAM), linear mixed-effects models (LMM), and Bayesian regression models (BRM) were independently employed to assess explanatory variables. The main results from our study were as follows: (i) tree age was the main explanatory variable for long-term growth variability; (ii) GAM, LMM, and BRM results consistently indicated climatic variables and CO 2 effects on G V and G H were weak, therefore evidence of recent climatic variability influence on beech annual growth rates was limited in the montane belt of the Italian peninsula; (iii) instead, significant positive nitrogen deposition (N dep ) effects were repeatedly observed in G V and G H ; the positive effects of N dep on canopy height growth rates, which tended to level off at N dep values greater than approximately 1.0 g m -2  y -1 , were interpreted as positive impacts on forest stand above-ground net productivity at the selected study sites. © 2018 John Wiley & Sons Ltd.

Social Inequality and Labor Force Participation.

ERIC Educational Resources Information Center

King, Jonathan

The labor force participation rates of whites, blacks, and Spanish-Americans, grouped by sex, are explained in a linear regression model fitted with 1970 U. S. Census data on Standard Metropolitan Statistical Area (SMSA). The explanatory variables are: average age, average years of education, vocational training rate, disabled rate, unemployment…

Fostering Hooks and Shifts: Tutorial Tactics for Guided Mathematical Discovery

ERIC Educational Resources Information Center

Abrahamson, Dor; Gutierrez, Jose; Charoenying, Timothy; Negrete, Andrea; Bumbacher, Engin

2012-01-01

How do instructors guide students to discover mathematical content? Are current explanatory models of pedagogical practice suitable to capture pragmatic essentials of discovery-based instruction? We examined videographed data from the implementation of a natural user interface design for proportions, so as to determine one constructivist tutor's…

Differentiated Success: Combining Theories to Explain Learning

ERIC Educational Resources Information Center

Jorgensen, Robyn; Larkin, Kevin

2015-01-01

This paper explores the value of different paradigms to explain dispositions towards mathematics among primary school students from different social backgrounds. As part of a larger project designed to elicit students' thinking and attitudes towards mathematics, we seek to develop an explanatory model for the socially-differentiated outcomes in…

Food Perceptions and Concerns of Aboriginal Women Coping with Gestational Diabetes in Winnipeg, Manitoba

ERIC Educational Resources Information Center

Neufeld, Hannah Tait

2011-01-01

Objective: To describe how Aboriginal women in an urban setting perceive dietary treatment recommendations associated with gestational diabetes mellitus (GDM). Design: Semi-structured explanatory model interviews explored Aboriginal women's illness experiences with GDM. Setting and Participants: Twenty-nine self-declared Aboriginal women who had…

Educational Research in Educational Practice: Predictors of Use

ERIC Educational Resources Information Center

Lysenko, Larysa V.; Abrami, Philip C.; Dagenais, Christian; Janosz, Michel

2014-01-01

This study investigates the predictors of school practitioners' (N = 2,425) use of educational research. The suggested model explained significantly but modestly the infrequent use of educational research by practitioners. Of the four factors in the study, "opinions about research" had the most explanatory power. The results are…

Revista de Investigacion Educativa, 1999 (Journal of Educational Research, 1999).

ERIC Educational Resources Information Center

Revista de Investigacion Educativa, 1999

1999-01-01

Articles in this volume, written in Spanish, focus on the following: intellectual style and academic performance; an explanatory integrated model of academic goals, learning strategies, and academic performance; a comparative situational study of drug addiction; early childhood depression and academic performance: a comparative study of patients…

The Relationship between the Emotional Intelligence of Secondary Public School Principals and School Performance

ERIC Educational Resources Information Center

Ashworth, Stephanie R.

2013-01-01

The study examined the relationship between secondary public school principals' emotional intelligence and school performance. The correlational study employed an explanatory sequential mixed methods model. The non-probability sample consisted of 105 secondary public school principals in Texas. The emotional intelligence characteristics of the…

Support, Belonging, Motivation, and Engagement in the College Classroom: A Mixed Method Study

ERIC Educational Resources Information Center

Zumbrunn, Sharon; McKim, Courtney; Buhs, Eric; Hawley, Leslie R.

2014-01-01

This explanatory sequential mixed methods study examined how belonging perceptions, academic motivation, and engagement might mediate the relationship between academic contextual characteristics and achievement using structural equation modeling and qualitative follow-up interviews with college students from a large, Midwestern university. In the…

Defining conservation priorities using fragmentation forecasts

Treesearch

David Wear; John Pye; Kurt H. Riitters

2004-01-01

Methods are developed for forecasting the effects of population and economic growth on the distribution of interior forest habitat. An application to the southeastern United States shows that models provide significant explanatory power with regard to the observed distribution of interior forest. Estimates for economic and biophysical variables are significant and...

"The Theory behind How Students Learn": Applying Developmental Theory to Research on Children's Historical Thinking

ERIC Educational Resources Information Center

Dulberg, Nancy

2005-01-01

Recent research on children's historical thinking has produced rich descriptions of instruction. However, the research literature is largely lacking a theoretical model of learning. This article asserts that developmental constructivist theory informs research design and interpretation, provides explanatory power, and promises more useful…

A Comparison of Mathematical Models of Fish Mercury Concentration as a Function of Atmospheric Mercury Deposition Rate and Watershed Characteristics

NASA Astrophysics Data System (ADS)

Smith, R. A.; Moore, R. B.; Shanley, J. B.; Miller, E. K.; Kamman, N. C.; Nacci, D.

2009-12-01

Mercury (Hg) concentrations in fish and aquatic wildlife are complex functions of atmospheric Hg deposition rate, terrestrial and aquatic watershed characteristics that influence Hg methylation and export, and food chain characteristics determining Hg bioaccumulation. Because of the complexity and incomplete understanding of these processes, regional-scale models of fish tissue Hg concentration are necessarily empirical in nature, typically constructed through regression analysis of fish tissue Hg concentration data from many sampling locations on a set of potential explanatory variables. Unless the data sets are unusually long and show clear time trends, the empirical basis for model building must be based solely on spatial correlation. Predictive regional scale models are highly useful for improving understanding of the relevant biogeochemical processes, as well as for practical fish and wildlife management and human health protection. Mechanistically, the logical arrangement of explanatory variables is to multiply each of the individual Hg source terms (e.g. dry, wet, and gaseous deposition rates, and residual watershed Hg) for a given fish sampling location by source-specific terms pertaining to methylation, watershed transport, and biological uptake for that location (e.g. SO4 availability, hill slope, lake size). This mathematical form has the desirable property that predicted tissue concentration will approach zero as all individual source terms approach zero. One complication with this form, however, is that it is inconsistent with the standard linear multiple regression equation in which all terms (including those for sources and physical conditions) are additive. An important practical disadvantage of a model in which the Hg source terms are additive (rather than multiplicative) with their modifying factors is that predicted concentration is not zero when all sources are zero, making it unreliable for predicting the effects of large future reductions in Hg deposition. In this paper we compare the results of using several different linear and non-linear models in an analysis of watershed and fish Hg data for 450 New England lakes. The differences in model results pertain to both their utility in interpreting methylation and export processes as well as in fisheries management.

Factors affecting hatch success of hawksbill sea turtles on Long Island, Antigua, West Indies.

PubMed

Ditmer, Mark Allan; Stapleton, Seth Patrick

2012-01-01

Current understanding of the factors influencing hawksbill sea turtle (Eretmochelys imbricata) hatch success is disparate and based on relatively short-term studies or limited sample sizes. Because global populations of hawksbills are heavily depleted, evaluating the parameters that impact hatch success is important to their conservation and recovery. Here, we use data collected by the Jumby Bay Hawksbill Project (JBHP) to investigate hatch success. The JBHP implements saturation tagging protocols to study a hawksbill rookery in Antigua, West Indies. Habitat data, which reflect the varied nesting beaches, are collected at egg deposition, and nest contents are exhumed and categorized post-emergence. We analyzed hatch success using mixed-model analyses with explanatory and predictive datasets. We incorporated a random effect for turtle identity and evaluated environmental, temporal and individual-based reproductive variables. Hatch success averaged 78.6% (SD: 21.2%) during the study period. Highly supported models included multiple covariates, including distance to vegetation, deposition date, individual intra-seasonal nest number, clutch size, organic content, and sand grain size. Nests located in open sand were predicted to produce 10.4 more viable hatchlings per clutch than nests located >1.5 m into vegetation. For an individual first nesting in early July, the fourth nest of the season yielded 13.2 more viable hatchlings than the initial clutch. Generalized beach section and inter-annual variation were also supported in our explanatory dataset, suggesting that gaps remain in our understanding of hatch success. Our findings illustrate that evaluating hatch success is a complex process, involving multiple environmental and individual variables. Although distance to vegetation and hatch success were inversely related, vegetation is an important component of hawksbill nesting habitat, and a more complete assessment of the impacts of specific vegetation types on hatch success and hatchling sex ratios is needed. Future research should explore the roles of sand structure, nest moisture, and local weather conditions.

Factors Affecting Hatch Success of Hawksbill Sea Turtles on Long Island, Antigua, West Indies

PubMed Central

Ditmer, Mark Allan; Stapleton, Seth Patrick

2012-01-01

Current understanding of the factors influencing hawksbill sea turtle (Eretmochelys imbricata) hatch success is disparate and based on relatively short-term studies or limited sample sizes. Because global populations of hawksbills are heavily depleted, evaluating the parameters that impact hatch success is important to their conservation and recovery. Here, we use data collected by the Jumby Bay Hawksbill Project (JBHP) to investigate hatch success. The JBHP implements saturation tagging protocols to study a hawksbill rookery in Antigua, West Indies. Habitat data, which reflect the varied nesting beaches, are collected at egg deposition, and nest contents are exhumed and categorized post-emergence. We analyzed hatch success using mixed-model analyses with explanatory and predictive datasets. We incorporated a random effect for turtle identity and evaluated environmental, temporal and individual-based reproductive variables. Hatch success averaged 78.6% (SD: 21.2%) during the study period. Highly supported models included multiple covariates, including distance to vegetation, deposition date, individual intra-seasonal nest number, clutch size, organic content, and sand grain size. Nests located in open sand were predicted to produce 10.4 more viable hatchlings per clutch than nests located >1.5 m into vegetation. For an individual first nesting in early July, the fourth nest of the season yielded 13.2 more viable hatchlings than the initial clutch. Generalized beach section and inter-annual variation were also supported in our explanatory dataset, suggesting that gaps remain in our understanding of hatch success. Our findings illustrate that evaluating hatch success is a complex process, involving multiple environmental and individual variables. Although distance to vegetation and hatch success were inversely related, vegetation is an important component of hawksbill nesting habitat, and a more complete assessment of the impacts of specific vegetation types on hatch success and hatchling sex ratios is needed. Future research should explore the roles of sand structure, nest moisture, and local weather conditions. PMID:22802928

The Effect of Local and Landscape-Level Characteristics on the Abundance of Forest Birds in Early-Successional Habitats during the Post-Fledging Season in Western Massachusetts

PubMed Central

Labbe, Michelle A.; King, David I.

2014-01-01

Many species of mature forest-nesting birds (“forest birds”) undergo a pronounced shift in habitat use during the post-fledging period and move from their forest nesting sites into areas of early-successional vegetation. Mortality is high during this period, thus understanding the resource requirements of post-fledging birds has implications for conservation. Efforts to identify predictors of abundance of forest birds in patches of early-successional habitats have so far been equivocal, yet these previous studies have primarily focused on contiguously forested landscapes and the potential for landscape-scale influences in more fragmented and modified landscapes is largely unknown. Landscape composition can have a strong influence on the abundance and productivity of forest birds during the nesting period, and could therefore affect the number of forest birds in the landscape available to colonize early-successional habitats during the post-fledging period. Therefore, the inclusion of landscape characteristics should increase the explanatory power of models of forest bird abundance in early-successional habitat patches during the post-fledging period. We examined forest bird abundance and body condition in relation to landscape and habitat characteristics of 15 early-successional sites during the post-fledging season in Massachusetts. The abundance of forest birds was influenced by within-patch habitat characteristics, however the explanatory power of these models was significantly increased by the inclusion of landscape fragmentation and the abundance of forest birds in adjacent forest during the nesting period for some species and age groups. Our findings show that including factors beyond the patch scale can explain additional variation in the abundance of forest birds in early-successional habitats during the post-fledging period. We conclude that landscape composition should be considered when siting early-successional habitat to maximize its benefit to forest birds during the post-fledging period, and should also be included in future investigations of post-fledging habitat use by forest birds. PMID:25170610

The effect of local and landscape-level characteristics on the abundance of forest birds in early-successional habitats during the post-fledging season in western Massachusetts.

PubMed

Labbe, Michelle A; King, David I

2014-01-01

Many species of mature forest-nesting birds ("forest birds") undergo a pronounced shift in habitat use during the post-fledging period and move from their forest nesting sites into areas of early-successional vegetation. Mortality is high during this period, thus understanding the resource requirements of post-fledging birds has implications for conservation. Efforts to identify predictors of abundance of forest birds in patches of early-successional habitats have so far been equivocal, yet these previous studies have primarily focused on contiguously forested landscapes and the potential for landscape-scale influences in more fragmented and modified landscapes is largely unknown. Landscape composition can have a strong influence on the abundance and productivity of forest birds during the nesting period, and could therefore affect the number of forest birds in the landscape available to colonize early-successional habitats during the post-fledging period. Therefore, the inclusion of landscape characteristics should increase the explanatory power of models of forest bird abundance in early-successional habitat patches during the post-fledging period. We examined forest bird abundance and body condition in relation to landscape and habitat characteristics of 15 early-successional sites during the post-fledging season in Massachusetts. The abundance of forest birds was influenced by within-patch habitat characteristics, however the explanatory power of these models was significantly increased by the inclusion of landscape fragmentation and the abundance of forest birds in adjacent forest during the nesting period for some species and age groups. Our findings show that including factors beyond the patch scale can explain additional variation in the abundance of forest birds in early-successional habitats during the post-fledging period. We conclude that landscape composition should be considered when siting early-successional habitat to maximize its benefit to forest birds during the post-fledging period, and should also be included in future investigations of post-fledging habitat use by forest birds.

Diagnosis-Based Risk Adjustment for Medicare Capitation Payments

PubMed Central

Ellis, Randall P.; Pope, Gregory C.; Iezzoni, Lisa I.; Ayanian, John Z.; Bates, David W.; Burstin, Helen; Ash, Arlene S.

1996-01-01

Using 1991-92 data for a 5-percent Medicare sample, we develop, estimate, and evaluate risk-adjustment models that utilize diagnostic information from both inpatient and ambulatory claims to adjust payments for aged and disabled Medicare enrollees. Hierarchical coexisting conditions (HCC) models achieve greater explanatory power than diagnostic cost group (DCG) models by taking account of multiple coexisting medical conditions. Prospective models predict average costs of individuals with chronic conditions nearly as well as concurrent models. All models predict medical costs far more accurately than the current health maintenance organization (HMO) payment formula. PMID:10172666

Modeling the frequency of opposing left-turn conflicts at signalized intersections using generalized linear regression models.

PubMed

Zhang, Xin; Liu, Pan; Chen, Yuguang; Bai, Lu; Wang, Wei

2014-01-01

The primary objective of this study was to identify whether the frequency of traffic conflicts at signalized intersections can be modeled. The opposing left-turn conflicts were selected for the development of conflict predictive models. Using data collected at 30 approaches at 20 signalized intersections, the underlying distributions of the conflicts under different traffic conditions were examined. Different conflict-predictive models were developed to relate the frequency of opposing left-turn conflicts to various explanatory variables. The models considered include a linear regression model, a negative binomial model, and separate models developed for four traffic scenarios. The prediction performance of different models was compared. The frequency of traffic conflicts follows a negative binominal distribution. The linear regression model is not appropriate for the conflict frequency data. In addition, drivers behaved differently under different traffic conditions. Accordingly, the effects of conflicting traffic volumes on conflict frequency vary across different traffic conditions. The occurrences of traffic conflicts at signalized intersections can be modeled using generalized linear regression models. The use of conflict predictive models has potential to expand the uses of surrogate safety measures in safety estimation and evaluation.

Self-rated health and health-strengthening factors in community-living frail older people.

PubMed

Ebrahimi, Zahra; Dahlin-Ivanoff, Synneve; Eklund, Kajsa; Jakobsson, Annika; Wilhelmson, Katarina

2015-04-01

The aim of this study was to analyse the explanatory power of variables measuring health-strengthening factors for self-rated health among community-living frail older people. Frailty is commonly constructed as a multi-dimensional geriatric syndrome ascribed to the multi-system deterioration of the reserve capacity in older age. Frailty in older people is associated with decreased physical and psychological well-being. However, knowledge about the experiences of health in frail older people is still limited. The design of the study was cross-sectional. The data were collected between October 2008 and November 2010 through face-to-face structured interviews with older people aged 65-96 years (N = 161). Binary logistic regression was used to analyse whether a set of explanatory relevant variables is associated with self-rated health. The results from the final model showed that satisfaction with one's ability to take care of oneself, having 10 or fewer symptoms and not feeling lonely had the best explanatory power for community-living frail older peoples' experiences of good health. The results indicate that a multi-disciplinary approach is desirable, where the focus should not only be on medical problems but also on providing supportive services to older people to maintain their independence and experiences of health despite frailty. © 2014 John Wiley & Sons Ltd.

Explanatory factors and predictors of fatigue in persons with rheumatoid arthritis: A longitudinal study.

PubMed

Feldthusen, Caroline; Grimby-Ekman, Anna; Forsblad-d'Elia, Helena; Jacobsson, Lennart; Mannerkorpi, Kaisa

2016-04-28

To investigate the impact of disease-related aspects on long-term variations in fatigue in persons with rheumatoid arthritis. Observational longitudinal study. Sixty-five persons with rheumatoid arthritis, age range 20-65 years, were invited to a clinical examination at 4 time-points during the 4 seasons. Outcome measures were: general fatigue rated on visual analogue scale (0-100) and aspects of fatigue assessed by the Bristol Rheumatoid Arthritis Fatigue Multidimensional Questionnaire. Disease-related variables were: disease activity (erythrocyte sedimentation rate), pain threshold (pressure algometer), physical capacity (six-minute walk test), pain (visual analogue scale (0-100)), depressive mood (Hospital Anxiety and Depression scale, depression subscale), personal factors (age, sex, body mass index) and season. Multivariable regression analysis, linear mixed effects models were applied. The strongest explanatory factors for all fatigue outcomes, when recorded at the same time-point as fatigue, were pain threshold and depressive mood. Self-reported pain was an explanatory factor for physical aspects of fatigue and body mass index contributed to explaining the consequences of fatigue on everyday living. For predicting later fatigue pain threshold and depressive mood were the strongest predictors. Pain threshold and depressive mood were the most important factors for fatigue in persons with rheumatoid arthritis.

Social support and clinical and functional outcome in people with schizophrenia.

PubMed

Vázquez Morejón, Antonio J; León Rubio, Jose Mª; Vázquez-Morejón, Raquel

2018-05-01

The impact of Social Support (SS) on the clinical and functional evolution of patients diagnosed with schizophrenia was studied from a multidimensional concept of SS in the framework of the vulnerability-stress model. In total, 152 patients diagnosed with schizophrenia according to the International Classification of Diseases, Tenth Edition (ICD-10) treated in a Community Mental Health Unit were assessed using the Mannheim Interview on Social Support (MISS) and the Brief Psychiatric Rating Scale (BPRS). Then they were followed up for 3 years with a final assessment for the period using the Social Functioning Scale. The impact of SS was explored in clinical and functional measurements with a multiple regression analysis in a 3-year longitudinal prospective design. The quality of Global Social Support (GSS) and satisfaction with GSS appeared to be protective factors from frequency and duration of hospital admissions, with explanatory intensity varying from 9% in survival time to relapse to 13% in number of relapses. Concerning functional measurements, GSS quantity, quality and satisfaction showed an explanatory power for several different dimensions of social functioning, varying from 12% in isolation to 20% in communication. The results confirm SS as a protective factor in the evolution of schizophrenia patients and enable the SS variables with the most explanatory power in their clinical and functional evolution to be identified.

Treatment needs and predictive capacity of explanatory variables of oral disease in young athletes with an intellectual disability in Europe and Eurasia.

PubMed

Fernandez, C; Descamps, I; Fabjanska, K; Kaschke, I; Marks, L

2016-03-01

To evaluate the oral condition and treatment needs of young athletes with intellectual disability (ID) from 53 countries of Europe and Eurasia who participated in the Special Olympics European Games held in Antwerp, October 2014. A cross- sectional study was undertaken with data collected through standardised procedures from consenting athletes under 21 years of age. Oral hygiene habits, reports of oral pain and presence of gingival signs, sealants, untreated caries and missing teeth were recorded. Data analysis was performed in SPSS to produce descriptive statistics and explanatory variables for untreated decay, and gingival signs of disease were tested with Multilevel Generalized Linear Mixed Models. Five hundred three athletes participated in this study (mean age 17 yrs). Untreated decay was recorded in 33.4% of the participants and 38.7% of them had signs of gingival disease. Absence of untreated decay was associated with lower chances of gingival signs, while absence of sealants was related with higher chances of untreated decay. There is consistent evidence of persistent need for increased promotion of oral health, as well as preventive and restorative treatment in young athletes with ID in Europe and Eurasia. Due to the limited predictive capacity of the studied variables for oral disease, further studies including other related factors are needed.

Risky online behaviors among adolescents: Longitudinal relations among problematic Internet use, cyberbullying perpetration, and meeting strangers online.

PubMed

Gámez-Guadix, Manuel; Borrajo, Erika; Almendros, Carmen

2016-03-01

Background and aims This study aims to analyze the cross-sectional and longitudinal relationship between three major risky online behaviors during adolescence: problematic Internet use, cyberbullying perpetration, and meeting strangers online. An additional objective was to study the role of impulsivity-irresponsibility as a possible explanatory variable of the relationships between these risky online behaviors. Methods The study sample was 888 adolescents that completed self-report measures at time 1 and time 2 with an interval of 6 months. Results The findings showed a significant cross-sectional relationship between the risky online behaviors analyzed. At the longitudinal level, problematic Internet use at time 1 predicted an increase in the perpetration of cyberbullying and meeting strangers online at time 2. Furthermore, meeting strangers online increased the likelihood of cyberbullying perpetration at time 2. Finally, when impulsivity-irresponsibility was included in the model as an explanatory variable, the relationships previously found remained significant. Discussion These results extend traditional problem behavior theory during adolescence, also supporting a relationship between different risky behaviors in cyberspace. In addition, findings highlighted the role of problematic Internet use, which increased the chances of developing cyberbullying perpetration and meeting strangers online over time. However, the results suggest a limited role of impulsivity-irresponsibility as an explicative mechanism. Conclusions The findings suggest that various online risk activities ought to be addressed together when planning assessment, prevention and intervention efforts.

Stigma, explanatory models and unmet needs of caregivers of children with developmental disorders in a low-income African country: a cross-sectional facility-based survey.

PubMed

Tilahun, Dejene; Hanlon, Charlotte; Fekadu, Abebaw; Tekola, Bethlehem; Baheretibeb, Yonas; Hoekstra, Rosa A

2016-04-27

Understanding the perspectives of caregivers of children with developmental disorders living in low-income countries is important to inform intervention programmes. The purpose of this study was to examine the stigma experiences, explanatory models, unmet needs, preferred interventions and coping mechanisms of caregivers of children with developmental disorders in Ethiopia. Participants comprised caregivers (n = 102) of children with developmental disorders attending two child mental health clinics in Addis Ababa. The majority (66.7%; n = 68) had a diagnosis of intellectual disability (ID); 34 children (33.3%) had autism spectrum disorder (ASD) as their primary diagnosis. All caregivers were administered a structured questionnaire via a face-to-face interview, which included an adaptation of the Family Interview Schedule, closed questions about socio-demographic characteristics, explanatory models of illness, type of interventions used or desired and coping strategies, and an open ended question regarding the family's unmet needs. Most caregivers reported experience of stigma: 43.1% worried about being treated differently, 45.1% felt ashamed about their child's condition and 26.7% made an effort to keep their child's condition secret. Stigma did not depend on the type of developmental disorder, the child's age or gender, or on the age or level of education of the caregiver (all p > 0.05). Reported stigma was significantly higher in caregivers who had sought traditional help (p < 0.01), provided supernatural explanations for their child's condition (p = .02) and in caregivers of Orthodox Christian faith (p = .03). Caregivers gave a mixture of biomedical explanations (e.g. head injury (30.4%) or birth complications (25.5%)) and supernatural explanations (e.g. spirit possession (40.2%) or sinful act (27.5%)) for their child's condition. The biggest reported unmet need was educational provision for their child (74.5%), followed by treatment by a health professional (47.1%), financial support (30.4%) and expert help to support their child's development (27.5%). Most caregivers reported that talking to health professionals (86.3%) and family (85.3%) helped them to cope. Many caregivers also used support from friends (76.5%) and prayer (57.8%) as coping mechanisms. This study highlights the stigma experienced by families caring for a child with a developmental disorder. Designing interventions appropriate for low-income settings that improve awareness about developmental disorders, decrease stigma, improve access to appropriate education and strengthen caregivers' support are needed.

Scientists' internal models of the greenhouse effect

NASA Astrophysics Data System (ADS)

Libarkin, J. C.; Miller, H.; Thomas, S. R.

2013-12-01

A prior study utilized exploratory factor analysis to identify models underlying drawings of the greenhouse effect made by entering university freshmen. This analysis identified four archetype models of the greenhouse effect that appear within the college enrolling population. The current study collected drawings made by 144 geoscientists, from undergraduate geoscience majors through professionals. These participants scored highly on a standardized assessment of climate change understanding and expressed confidence in their understanding; many also indicated that they teach climate change in their courses. Although geoscientists held slightly more sophisticated greenhouse effect models than entering freshmen, very few held complete, explanatory models. As with freshmen, many scientists (44%) depict greenhouse gases in a layer in the atmosphere; 52% of participants depicted this or another layer as a physical barrier to escaping energy. In addition, 32% of participants indicated that incoming light from the Sun remains unchanged at Earth's surface, in alignment with a common model held by students. Finally, 3-20% of scientists depicted physical greenhouses, ozone, or holes in the atmosphere, all of which correspond to non-explanatory models commonly seen within students and represented in popular literature. For many scientists, incomplete models of the greenhouse effect are clearly enough to allow for reasoning about climate change. These data suggest that: 1) better representations about interdisciplinary concepts, such as the greenhouse effect, are needed for both scientist and public understanding; and 2) the scientific community needs to carefully consider how much understanding of a model is needed before necessary reasoning can occur.

A database for propagation models

NASA Technical Reports Server (NTRS)

Kantak, Anil V.; Suwitra, Krisjani; Le, Choung

1994-01-01

A database of various propagation phenomena models that can be used by telecommunications systems engineers to obtain parameter values for systems design is presented. This is an easy-to-use tool and is currently available for either a PC using Excel software under Windows environment or a Macintosh using Excel software for Macintosh. All the steps necessary to use the software are easy and many times self-explanatory; however, a sample run of the CCIR rain attenuation model is presented.

Distancing, not embracing, the Distancing-Embracing model of art reception.

PubMed

Davies, Stephen

2017-01-01

Despite denials in the target article, the Distancing-Embracing model appeals to compensatory ideas in explaining the appeal of artworks that elicit negative affect. The model also appeals to the deflationary effects of psychological distancing. Having pointed to the famous rejection in the 1960s of the view that aesthetic experience involves psychological distancing, I suggest that "distance" functions here as a weak metaphor that cannot sustain the explanatory burden the theory demands of it.

Explanatory Variables Associated with Campylobacter and Escherichia coli Concentrations on Broiler Chicken Carcasses during Processing in Two Slaughterhouses.

PubMed

Pacholewicz, Ewa; Swart, Arno; Wagenaar, Jaap A; Lipman, Len J A; Havelaar, Arie H

2016-12-01

This study aimed at identifying explanatory variables that were associated with Campylobacter and Escherichia coli concentrations throughout processing in two commercial broiler slaughterhouses. Quantative data on Campylobacter and E. coli along the processing line were collected. Moreover, information on batch characteristics, slaughterhouse practices, process performance, and environmental variables was collected through questionnaires, observations, and measurements, resulting in data on 19 potential explanatory variables. Analysis was conducted separately in each slaughterhouse to identify which variables were related to changes in concentrations of Campylobacter and E. coli during the processing steps: scalding, defeathering, evisceration, and chilling. Associations with explanatory variables were different in the slaughterhouses studied. In the first slaughterhouse, there was only one significant association: poorer uniformity of the weight of carcasses within a batch with less decrease in E. coli concentrations after defeathering. In the second slaughterhouse, significant statistical associations were found with variables, including age, uniformity, average weight of carcasses, Campylobacter concentrations in excreta and ceca, and E. coli concentrations in excreta. Bacterial concentrations in excreta and ceca were found to be the most prominent variables, because they were associated with concentration on carcasses at various processing points. Although the slaughterhouses produced specific products and had different batch characteristics and processing parameters, the effect of the significant variables was not always the same for each slaughterhouse. Therefore, each slaughterhouse needs to determine its particular relevant measures for hygiene control and process management. This identification could be supported by monitoring changes in bacterial concentrations during processing in individual slaughterhouses. In addition, the possibility that management and food handling practices in slaughterhouses contribute to the differences in bacterial contamination between slaughterhouses needs further investigation.

Barriers and Explanatory Mechanisms of Delays in the Patient and Diagnosis Intervals of Care for Breast Cancer in Mexico.

PubMed

Unger-Saldaña, Karla; Ventosa-Santaulària, Daniel; Miranda, Alfonso; Verduzco-Bustos, Guillermo

2018-04-01

Most breast cancer patients in low- and middle-income settings are diagnosed at advanced stages due to lengthy intervals of care. This study aimed to understand the mechanisms through which delays occur in the patient interval and diagnosis interval of care. We conducted a cross-sectional survey including 886 patients referred to four major public cancer hospitals in Mexico City. Based in a conceptual model of help-seeking behavior, a path analysis strategy was used to identify the relationships between explanatory factors of patient delay and diagnosis delay. The patient and the diagnosis intervals were greater than 3 months in 20% and 65% of participants, respectively. We present explanatory models for each interval and the interrelationship between the associated factors. The patient interval was longer among women who were single, interpreted their symptoms as not worrisome, concealed symptoms, and perceived a lack of financial resources and the difficulty of missing a day of work as barriers to seek care. These barriers were more commonly perceived among patients who were younger, had lower socioeconomic status, and lived outside of Mexico City. The diagnosis interval was longer among those who used several different health services prior to the cancer hospital and perceived medical errors in these services. More health services were used among those who perceived errors and long waiting times for appointments, and who first consulted private services. Our findings support the relevance of strengthening early cancer diagnosis strategies, especially the improvement of quality of primary care and expedited referral routes to cancer services. This study's findings suggest that policy in low- and middle-income countries (LMICs) should be directed toward reducing delays in diagnosis, before the implementation of mammography screening programs. The results suggest several factors susceptible to early diagnosis interventions. To reduce patient delays, the usually proposed intervention of awareness promotion could better work in LMIC contexts if the message goes beyond the advertising of screening mammography to encourage the recognition of potential cancer symptoms and sharing of symptoms with significant others. To reduce diagnosis delay, efforts should focus on strengthening the quality of public primary care services and improving referral routes to cancer care centers. © AlphaMed Press 2017.

World Culture in the Capitalist World-System in Transition

ERIC Educational Resources Information Center

Griffiths, Tom G.; Arnove, Robert F.

2015-01-01

World culture theory (WCT) offers an explanatory framework for macro-level comparative analyses of systems of mass education, including their structures, accompanying policies and their curricular and pedagogical practices. WCT has contributed to broader efforts to overcome methodological nationalism in comparative research. In this paper, we…

School Building Finishing and Economy. The School Building Economy Series, No. 6.

ERIC Educational Resources Information Center

Connecticut State Dept. of Education, Hartford.

Materials, elements, and methods of economical school construction are illustrated through explanatory outlines and accompany photographs and diagrams. Finishing elements covered include--(1) finished floorings, (2) ceilings and acoustical finishes, (3) carpentry and millwork, (4) chalkboards and tackboards, (5) toilet partitions, (6) finishing…

Explanation and Prediction: Building a Unified Theory of Librarianship, Concept and Review.

ERIC Educational Resources Information Center

McGrath, William E.

2002-01-01

Develops a comprehensive, unified, explanatory theory of librarianship by first making an analogy to the unification of the fundamental forces of nature. Topics include dependent and independent variables; publishing; acquisitions; classification and organization of knowledge; storage, preservation, and collection management; collections; and…

Puerto Rican Perspectives.

ERIC Educational Resources Information Center

Mapp, Edward, Ed.

The contents of this compendium are organized in four parts, as follows. Part one, "From Education," includes the following essays: "A Positive View of Bilingualism," Bejamin Pacheco; "Puerto Rican Children and the New York City Public Schools," Luis Fuentes; "Why Puerto Rican Students Drop Out of School: An Explanatory Analysis," Alexander…

Impact of managed care on physicians' decisions to manipulate reimbursement rules: an explanatory model.

PubMed

VanGeest, Jonathan; Weiner, Saul; Johnson, Timothy; Cummins, Deborah

2007-07-01

To develop and test an explanatory model of the impact of managed care on physicians' decisions to manipulate reimbursement rules for patients. A self-administered mailed questionnaire of a national random sample of 1124 practicing physicians in the USA. Structural equation modelling was used. The main outcome measure assessed whether or not physicians had manipulated reimbursement rules (such as exaggerated the severity of patients conditions, changed billing diagnoses, or reported signs or symptoms that the patients did not have) to help patients secure coverage for needed treatment or services. The response rate was 64% (n = 720). Physicians' decisions to manipulate reimbursement rules for patients are directly driven not only by ethical beliefs about gaming the system but also by requests from patients, the perception of insufficient time to deliver care, and the proportion of Medicaid patients. Covert advocacy is also the indirect result of utilization review hassles, primary care specialty, and practice environment. Managed care is not just a set of rules that physicians choose to follow or disobey, but an environment of competing pressures from patients, purchasers, and high workload. Reimbursement manipulation is a response to that environment, rather than simply a reflection of individual physicians' values.

Land Use, Land Conservation, and Wind Energy Development Outcomes in New England

NASA Astrophysics Data System (ADS)

Weimar, William Cameron

This dissertation provides three independent research inquiries. The first examines how inter-governmental policy, site-specific, and social factors lead to the success, prolonged delay, or failure of inland wind power projects in New England. The three case studies examined include the 48 megawatt Glebe Mountain Wind Farm proposal in southern Vermont, the 30 megawatt Hoosac Wind Farm in western Massachusetts, and the 24 megawatt Lempster Wind Farm in southern New Hampshire. To ascertain why the project outcomes varied, 45 semi-structured interviews were conducted with a range of stakeholders, including wind development firms, utility companies, state regulatory agencies, regional planning commissions, town officials, land conservation organizations, and opposition groups. The second study establishes a comprehensive set of thirty-seven explanatory variables to determine the amount of suitable land and the corresponding electricity generation potential within the prime wind resource areas of Western Massachusetts. The explanatory variables are incorporated into Boolean GIS suitability models which represent the two divergent positions towards wind power development in Massachusetts, and a third, balanced model. The third study determines that exurban residential development is not the only land use factor that reduces wind power development potential in Western Massachusetts. A set of Boolean GIS models for 1985 and 2009 find the onset of conservation easements on private lands having the largest impact. During this 25 year period a combination of land use conversion and land conservation has reduced the access to prime wind resource areas by 18% (11,601 hectares), an equivalent loss of 5,800--8,700 GWh/year of zero carbon electricity generation. The six main findings from this research are: (1) Visual aesthetics remain the main factor of opposition to specific projects; (2) The Not-in-my Backyard debate for wind power remains unsettled; (3) Widespread support exists for regional land use energy plans; (4) The wind resources of Western Massachusetts can significantly contribute to the state's current renewable portfolio standard while balancing conservation and renewable energy development objectives; However, (5) a combination of exurban residential development and conservation easements significantly reduces wind power development potential over time; and (6) a need exists to legally define wind as a publicly beneficial resource.

Watershed regressions for pesticides (warp) models for predicting atrazine concentrations in Corn Belt streams

USGS Publications Warehouse

Stone, Wesley W.; Gilliom, Robert J.

2012-01-01

Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region-specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP-CB) were developed for annual maximum moving-average (14-, 21-, 30-, 60-, and 90-day durations) and annual 95th-percentile atrazine concentrations in streams of the Corn Belt region. The WARP-CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model-development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model-development sites. The WARP-CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine-use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP-CB models. The WARP-CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine-use intensities of 17 kg/km2 of watershed area or greater.

Antarctic Meteorite Location and Mapping Project (AMLAMP): Antarctic meteorite location map series explanatory text and user's guide to AMLAMP data

NASA Technical Reports Server (NTRS)

Schutt, J.; Fessler, B.; Cassidy, W. A.

1993-01-01

This technical report is an update to LPI Technical Report 89-02, which contained data and information that was current to May 1987. Since that time approximately 4000 new meteorites have been collected, mapped, and characterized, mainly from the numerous ice fields in the Allan Hills-David Glacier region, from the Pecora Escarpment and Moulton Escarpment in the Thiel Mountains-Patuxent region, the Wisconsin Range region, and from the Beardmore region. Meteorite location maps for ice fields from these regions have been produced and are available. This report includes explanatory texts for the maps of new areas and provides information on updates of maps of the areas covered in LPI Technical Report 89-02. Sketch maps and description of locales that have been searched and have yielded single or few meteorites are also included. The meteorite listings for all the ice fields have been updated to include any classification changes and new meteorites recovered from ice fields in the Allan Hills-David Glacier region since 1987. The text has been reorganized and minor errors in the original report have been corrected. Computing capabilities have improved immensely since the early days of this project. Current software and hardware allow easy access to data over computer networks. With various commercial software packages, the data can be used many different ways, including database creation, statistics, and mapping. The databases, explanatory texts, and the plotter files used to produce the meteorite location maps are available through a computer network. Information on how to access AMLAMP data, its formats, and ways it can be used are given in the User's Guide to AMLAMP Data section. Meteorite location maps and thematic maps may be ordered from the Lunar and Planetary Institute. Ordering information is given in Appendix A.

Short-Term Energy Outlook Model Documentation: Macro Bridge Procedure to Update Regional Macroeconomic Forecasts with National Macroeconomic Forecasts

EIA Publications

2010-01-01

The Regional Short-Term Energy Model (RSTEM) uses macroeconomic variables such as income, employment, industrial production and consumer prices at both the national and regional1 levels as explanatory variables in the generation of the Short-Term Energy Outlook (STEO). This documentation explains how national macroeconomic forecasts are used to update regional macroeconomic forecasts through the RSTEM Macro Bridge procedure.

Using a Market Ratio Factor in Faculty Salary Equity Studies. AIR Professional File. Number 103, Spring 2007

ERIC Educational Resources Information Center

Luna, Andrew L.

2007-01-01

The purpose of this study was to determine if a market ratio factor was a better predictor of faculty salaries than the use of k-1 dummy variables representing the various disciplines. This study used two multiple regression analyses to develop an explanatory model to determine which model might best explain faculty salaries. A total of 20 out of…

The psychological interdependence of family, school, and bureaucracy in Japan.

PubMed

Kiefer, C W

1970-02-01

The Japanese "examination hell" phenomenon is viewed as a series of crisis rites through which the child passes from family-centered to peer group - centered values in a "particularistic" society. It is held that this model has greater explanatory power than the "minimization of competition" model proposed by others and that it also helps to explain the phenomenon of student radicalism and centrifugal relationships in middle-class communities.

An Analysis of the Relationship between the Organizational Culture and the Performance of Staff Work Groups in Schools and the Development of an Explanatory Model

ERIC Educational Resources Information Center

James, Chris; Connolly, Michael

2009-01-01

This article analyses the concept of organizational culture and the relationship between the organizational culture and the performance of staff work groups in schools. The article draws upon a study of 12 schools in Wales, UK, which despite being in disadvantaged settings have high levels of pupil attainment. A model is developed linking the…

Afference copy as a quantitative neurophysiological model for consciousness.

PubMed

Cornelis, Hugo; Coop, Allan D

2014-06-01

Consciousness is a topic of considerable human curiosity with a long history of philosophical analysis and debate. We consider there is nothing particularly complicated about consciousness when viewed as a necessary process of the vertebrate nervous system. Here, we propose a physiological "explanatory gap" is created during each present moment by the temporal requirements of neuronal activity. The gap extends from the time exteroceptive and proprioceptive stimuli activate the nervous system until they emerge into consciousness. During this "moment", it is impossible for an organism to have any conscious knowledge of the ongoing evolution of its environment. In our schematic model, a mechanism of "afference copy" is employed to bridge the explanatory gap with consciously experienced percepts. These percepts are fabricated from the conjunction of the cumulative memory of previous relevant experience and the given stimuli. They are structured to provide the best possible prediction of the expected content of subjective conscious experience likely to occur during the period of the gap. The model is based on the proposition that the neural circuitry necessary to support consciousness is a product of sub/preconscious reflexive learning and recall processes. Based on a review of various psychological and neurophysiological findings, we develop a framework which contextualizes the model and briefly discuss further implications.

Human influence on California fire regimes.

PubMed

Syphard, Alexandra D; Radeloff, Volker C; Keeley, Jon E; Hawbaker, Todd J; Clayton, Murray K; Stewart, Susan I; Hammer, Roger B

2007-07-01

Periodic wildfire maintains the integrity and species composition of many ecosystems, including the mediterranean-climate shrublands of California. However, human activities alter natural fire regimes, which can lead to cascading ecological effects. Increased human ignitions at the wildland-urban interface (WUI) have recently gained attention, but fire activity and risk are typically estimated using only biophysical variables. Our goal was to determine how humans influence fire in California and to examine whether this influence was linear, by relating contemporary (2000) and historic (1960-2000) fire data to both human and biophysical variables. Data for the human variables included fine-resolution maps of the WUI produced using housing density and land cover data. Interface WUI, where development abuts wildland vegetation, was differentiated from intermix WUI, where development intermingles with wildland vegetation. Additional explanatory variables included distance to WUI, population density, road density, vegetation type, and ecoregion. All data were summarized at the county level and analyzed using bivariate and multiple regression methods. We found highly significant relationships between humans and fire on the contemporary landscape, and our models explained fire frequency (R2 = 0.72) better than area burned (R2 = 0.50). Population density, intermix WUI, and distance to WUI explained the most variability in fire frequency, suggesting that the spatial pattern of development may be an important variable to consider when estimating fire risk. We found nonlinear effects such that fire frequency and area burned were highest at intermediate levels of human activity, but declined beyond certain thresholds. Human activities also explained change in fire frequency and area burned (1960-2000), but our models had greater explanatory power during the years 1960-1980, when there was more dramatic change in fire frequency. Understanding wildfire as a function of the spatial arrangement of ignitions and fuels on the landscape, in addition to nonlinear relationships, will be important to fire managers and conservation planners because fire risk may be related to specific levels of housing density that can be accounted for in land use planning. With more fires occurring in close proximity to human infrastructure, there may also be devastating ecological impacts if development continues to grow farther into wildland vegetation.

Human influence on California fire regimes

USGS Publications Warehouse

Syphard, A.D.; Radeloff, V.C.; Keeley, J.E.; Hawbaker, T.J.; Clayton, M.K.; Stewart, S.I.; Hammer, R.B.

2007-01-01

Periodic wildfire maintains the integrity and species composition of many ecosystems, including the mediterranean-climate shrublands of California. However, human activities alter natural fire regimes, which can lead to cascading ecological effects. Increased human ignitions at the wildland-urban interface (WUI) have recently gained attention, but fire activity and risk are typically estimated using only biophysical variables. Our goal was to determine how humans influence fire in California and to examine whether this influence was linear, by relating contemporary (2000) and historic (1960-2000) fire data to both human and biophysical variables. Data for the human variables included fine-resolution maps of the WUI produced using housing density and land cover data. Interface WUI, where development abuts wildland vegetation, was differentiated from intermix WUI, where development intermingles with wildland vegetation. Additional explanatory variables included distance to WUI, population density, road density, vegetation type, and ecoregion. All data were summarized at the county level and analyzed using bivariate and multiple regression methods. We found highly significant relationships between humans and fire on the contemporary landscape, and our models explained fire frequency (R2 = 0.72) better than area burned (R2 = 0.50). Population density, intermix WUI, and distance to WUI explained the most variability in fire frequency, suggesting that the spatial pattern of development may be an important variable to consider when estimating fire risk. We found nonlinear effects such that fire frequency and area burned were highest at intermediate levels of human activity, but declined beyond certain thresholds. Human activities also explained change in fire frequency and area burned (1960-2000), but our models had greater explanatory power during the years 1960-1980, when there was more dramatic change in fire frequency. Understanding wildfire as a function of the spatial arrangement of ignitions and fuels on the landscape, in addition to nonlinear relationships, will be important to fire managers and conservation planners because fire risk may be related to specific levels of housing density that can be accounted for in land use planning. With more fires occurring in close proximity to human infrastructure, there may also be devastating ecological impacts if development continues to grow farther into wildland vegetation. ?? 2007 by the Ecological Society of America.

Modeling Passive Propagation of Malwares on the WWW

NASA Astrophysics Data System (ADS)

Chunbo, Liu; Chunfu, Jia

Web-based malwares host in websites fixedly and download onto user's computers automatically while users browse. This passive propagation pattern is different from that of traditional viruses and worms. A propagation model based on reverse web graph is proposed. In this model, propagation of malwares is analyzed by means of random jump matrix which combines orderness and randomness of user browsing behaviors. Explanatory experiments, which has single or multiple propagation sources respectively, prove the validity of the model. Using this model, people can evaluate the hazardness of specified websites and take corresponding countermeasures.

Modeling of the financial market using the two-dimensional anisotropic Ising model

NASA Astrophysics Data System (ADS)

Lima, L. S.

2017-09-01

We have used the two-dimensional classical anisotropic Ising model in an external field and with an ion single anisotropy term as a mathematical model for the price dynamics of the financial market. The model presented allows us to test within the same framework the comparative explanatory power of rational agents versus irrational agents with respect to the facts of financial markets. We have obtained the mean price in terms of the strong of the site anisotropy term Δ which reinforces the sensitivity of the agent's sentiment to external news.

Selection of relevant input variables in storm water quality modeling by multiobjective evolutionary polynomial regression paradigm

NASA Astrophysics Data System (ADS)

Creaco, E.; Berardi, L.; Sun, Siao; Giustolisi, O.; Savic, D.

2016-04-01

The growing availability of field data, from information and communication technologies (ICTs) in "smart" urban infrastructures, allows data modeling to understand complex phenomena and to support management decisions. Among the analyzed phenomena, those related to storm water quality modeling have recently been gaining interest in the scientific literature. Nonetheless, the large amount of available data poses the problem of selecting relevant variables to describe a phenomenon and enable robust data modeling. This paper presents a procedure for the selection of relevant input variables using the multiobjective evolutionary polynomial regression (EPR-MOGA) paradigm. The procedure is based on scrutinizing the explanatory variables that appear inside the set of EPR-MOGA symbolic model expressions of increasing complexity and goodness of fit to target output. The strategy also enables the selection to be validated by engineering judgement. In such context, the multiple case study extension of EPR-MOGA, called MCS-EPR-MOGA, is adopted. The application of the proposed procedure to modeling storm water quality parameters in two French catchments shows that it was able to significantly reduce the number of explanatory variables for successive analyses. Finally, the EPR-MOGA models obtained after the input selection are compared with those obtained by using the same technique without benefitting from input selection and with those obtained in previous works where other data-modeling techniques were used on the same data. The comparison highlights the effectiveness of both EPR-MOGA and the input selection procedure.

Exploring the explaining quality of physics online explanatory videos

NASA Astrophysics Data System (ADS)

Kulgemeyer, Christoph; Peters, Cord H.

2016-11-01

Explaining skills are among the most important skills educators possess. Those skills have also been researched in recent years. During the same period, another medium has additionally emerged and become a popular source of information for learners: online explanatory videos, chiefly from the online video sharing website YouTube. Their content and explaining quality remain to this day mostly unmonitored, as well is their educational impact in formal contexts such as schools or universities. In this study, a framework for explaining quality, which has emerged from surveying explaining skills in expert-novice face-to-face dialogues, was used to explore the explaining quality of such videos (36 YouTube explanatory videos on Kepler’s laws and 15 videos on Newton’s third law). The framework consists of 45 categories derived from physics education research that deal with explanation techniques. YouTube provides its own ‘quality measures’ based on surface features including ‘likes’, views, and comments for each video. The question is whether or not these measures provide valid information for educators and students if they have to decide which video to use. We compared the explaining quality with those measures. Our results suggest that there is a correlation between explaining quality and only one of these measures: the number of content-related comments.

The Current Status of Modular Coordination. A Research Correlation Conference of Building Research Institute, Division of Engineering and Industrial Research (Fall 1959).

ERIC Educational Resources Information Center

National Academy of Sciences - National Research Council, Washington, DC.

Publication of conference presentations include--(1) a brief review of current modular standard development, (2) the statistical status of modular practice, (3) availability of modular products, and (4) educational programs on modular coordination. Included are--(1) explanatory diagrams, (2) text of an open panel discussion, and (3) a list of…

Episodic acidification of small streams in the northeastern united states: Fish mortality in field bioassays

USGS Publications Warehouse

Van Sickle, J.; Baker, J.P.; Simonin, H.A.; Baldigo, Barry P.; Kretser, W.A.; Sharpe, W.E.

1996-01-01

In situ bioassays were performed as part of the Episodic Response Project, to evaluate the effects of episodic stream acidification on mortality of brook trout (Salvelinus fontinalis) and forage fish species. We report the results of 122 bioassays in 13 streams of the three study regions: the Adirondack mountains of New York, the Catskill mountains of New York, and the Northern Appalachian Plateau of Pennsylvania. Bioassays during acidic episodes had significantly higher mortality than did bioassays conducted under nonacidic conditions, but there was little difference in mortality rates in bioassays experiencing acidic episodes and those experiencing acidic conditions throughout the test period. Multiple logistic regression models were used to relate bioassay mortality rates to summary statistics of time-varying stream chemistry (inorganic monomeric aluminum, calcium, pH, and dissolved organic carbon) estimated for the 20-d bioassay periods. The large suite of candidate regressors also included biological, regional, and seasonal factors, as well as several statistics summarizing various features of aluminum exposure duration and magnitude. Regressor variable selection and model assessment were complicated by multicol-linearity and overdispersion. For the target fish species, brook trout, bioassay mortality was most closely related to time-weighted median inorganic aluminum. Median Ca and minimum pH offered additional explanatory power, as did stream-specific aluminum responses. Due to high multicollinearity, the relative importance of different aluminum exposure duration and magnitude variables was difficult to assess, but these variables taken together added no significant explanatory power to models already containing median aluminum. Between 59 and 79% of the variation in brook trout mortality was explained by models employing between one and five regressors. Simpler models were developed for smaller sets of bioassays that tested slimy and mottled sculpin (Cottus cognatus and C. bairdi) as well as blacknose dace (Rhinichthys atratulus). For these forage species a single inorganic aluminum exposure variable successfully accounted for 86-98% of the observed mortality. Even though field bioassays showed evidence of multiple toxicity factors, model results suggest that adequate mortality predictions can be obtained from a single index of inorganic Al concentrations during exposure periods.

Comments in reply: new directions in migration research.

PubMed

Shaw, R P

1986-01-01

The author comments on a review of his recent book NEW DIRECTIONS IN MIGRATION RESEARCH and reflects on theory and model specification, problems of estimation and statistical inference, realities of temporal and spatial heterogeneity, choices of explanatory variables, and the importance of broader political issues in migration studies. A core hypothesis is that market forces have declined as influences on internal migration in Canada over the last 30 years. Theoretical underpinnings include declining relevance of wage considerations in the decision to migrate on the assumption that marginal utility of money diminishes and marginal utility of leisure increases as society becomes wealthier. The author perceives the human capital model to have limitations and is especially troubled by the "as if" clause--that all migrants behave "as if" they calculate benefits and risks with equal rigor. The author has "shadowed" and not quantified the costs involved. He implies that normative frameworks for future migration research and planning should be established.

Cultural differences in the experience of everyday symptoms: a comparative study of South Asian and European American women.

PubMed

Karasz, Alison; Dempsey, Kara; Fallek, Ronit

2007-12-01

This paper describes a study of medically ambiguous symptoms in two contrasting cultural groups. The study combined a qualitative, meaning-centered approach with a structured coding system and comparative design. Thirty-six South Asian immigrants and thirty-seven European Americans participated in a semistructured health history interview designed to elicit conceptual models of medically unexplained illness. The groups reported similar symptoms, but the organization of illness episodes and explanatory models associated with these episodes differed sharply. A variety of cultural variables and processes is proposed to account for observed differences, including somatization, the role of local illness categories, and the divergent core conflicts and values associated with gender roles. It is argued that the comparative design of the study provided insights that could not have been achieved through the study of a single group.

Personality and Depression: Explanatory Models and Review of the Evidence

PubMed Central

Klein, Daniel N.; Kotov, Roman; Bufferd, Sara J.

2012-01-01

Understanding the association between personality and depression has implications for elucidating etiology and comorbidity, identifying at-risk individuals, and tailoring treatment. We discuss seven major models that have been proposed to explain the relation between personality and depression, and we review key methodological issues, including study design, the heterogeneity of mood disorders, and the assessment of personality. We then selectively review the extensive empirical literature on the role of personality traits in depression in adults and children. Current evidence suggests that depression is linked to traits such as neuroticism/negative emotionality, extraversion/positive emotionality, and conscientiousness. Moreover, personality characteristics appear to contribute to the onset and course of depression through a variety of pathways. Implications for prevention and prediction of treatment response are discussed, as well as specific considerations to guide future research on the relation between personality and depression. PMID:21166535

The cumulative effects of life event, personal and social resources on subjective well-being of elderly widowers.

PubMed

Balaswamy, S; Richardson, V E

2001-01-01

A multidimensional Life Stress Model was used to test the independent contributions of background characteristics, personal resources, life event, and environmental influences on 200 widowers' levels of well-being, measured by the Affect Balance Scale. Stepwise regression analyses revealed that environmental resources were unrelated to negative affect which is influenced more by the life event and personal resource variables. The environmental resource variables, particularly interactions with friends and neighbors, mostly influenced positive affect. The explanatory model for well-being included multiple variables and explained 33 percent of the variance. Although background characteristics had the greatest impact, absence of hospitalization, higher mastery, higher self-esteem, contacts with friends, and interaction with neighbors enhanced well-being. The results support previous speculations on the importance of positive exchanges for positive affect. African-American widowers showed higher levels of well-being than Caucasian widowers did. The results advance knowledge about differences among elderly men.

Nonparametric instrumental regression with non-convex constraints

NASA Astrophysics Data System (ADS)

Grasmair, M.; Scherzer, O.; Vanhems, A.

2013-03-01

This paper considers the nonparametric regression model with an additive error that is dependent on the explanatory variables. As is common in empirical studies in epidemiology and economics, it also supposes that valid instrumental variables are observed. A classical example in microeconomics considers the consumer demand function as a function of the price of goods and the income, both variables often considered as endogenous. In this framework, the economic theory also imposes shape restrictions on the demand function, such as integrability conditions. Motivated by this illustration in microeconomics, we study an estimator of a nonparametric constrained regression function using instrumental variables by means of Tikhonov regularization. We derive rates of convergence for the regularized model both in a deterministic and stochastic setting under the assumption that the true regression function satisfies a projected source condition including, because of the non-convexity of the imposed constraints, an additional smallness condition.

Techniques used to identify tornado producing thunderstorms using geosynchronous satellite data

NASA Technical Reports Server (NTRS)

Schrab, Kevin J.; Anderson, Charles E.; Monahan, John F.

1992-01-01

Satellite imagery in the outbreak region in the time prior to and during tornado occurrence was examined in detail to obtain descriptive characteristics of the anvil plume. These characteristics include outflow strength (UMAX), departure of anvil centerline from the storm relative ambient wind (MDA), storm relative ambient wind (SRAW), and maximum surface vorticity (SFCVOR). It is shown that by using satellite derived parameters which characterize the flow field in the anvil region, the occurrence and intensity of tornadoes, which the parent thunderstorm produces, can be identified. Analysis of the censored regression models revealed that the five explanatory variables (UMAX, MDA, SRAW, UMAX-2, and SFCVOR) were all significant predictors in the identification of tornadic intensity of a particular thunderstorm.

[Chronic low back pain: from the uncertain medical diagnosis to the profane etiologies].

PubMed

Mbarga, Josiane; Pichonnaz, Claude; Foley, Rose-Anna; Ancey, Céline

2018-04-18

This qualitative research article is based on interviews with 20 participants to a low back pain rehabilitation program in a Swiss hospital. It shows that, in the absence of the obvious cause that can explain pain, patients construct their own interpretations and explanations in order to give meaning to their experience. Their explanatory models mainly include the lifestyle and the physical aspects related to the body function, what leaves little room for the psychosocial component. Their interpretation is consequently discordant with the current medical approach, which considers that chronic low back pain results from bio-psycho-social factors. This discrepancy implies negotiation between patients and professionals about the objectives to achieve in order to treat pain.

Physical and human dimensions of deforestation in Amazonia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skole, D.L.; Chomentowski, W.H.; Salas W.A.

1994-05-01

In the Brazilian Amazon, regional trends are influenced by large scale external forces but mediated by local conditions. Tropical deforestation has a large influence on global hydrology, climate and biogeochemical cycles, but understanding is inadequate because of a lack of accurate measurements of rate, geographic extent and spatial patterns and lack of insight into its causes including interrelated social, economic and environmental factors. This article proposes an interdisciplinary approach for analyzing tropical deforestation in the Brazilian Amazon. The first part shows how deforestation can be measured from satellite remote sensing and sociodemographic and economic data. The second part proposes anmore » explanatory model, considering the relationship among deforestation and large scale social, economic, and institutional factors. 43 refs., 8 figs.« less

Students, Graduates, and Dropouts in the Labor Market, October 1975. Special Labor Force Report 199.

ERIC Educational Resources Information Center

Young, Anne McD.

1976-01-01

This report by the U.S. Department of Labor, Bureau of Statistics covers youth employment and education, and their interwoven causes and results. Numerous statistical charts and explanatory notes are included. Factors, such as age, race, sex and status, are analyzed. (MML)

KURDISH READERS. PART III, KURDISH SHORT STORIES.

ERIC Educational Resources Information Center

ABDULLA, JAMAL JALAL; MCCARUS, ERNEST N.

THE SIX STORIES IN THIS COLLECTION ARE WRITTEN IN THE KURDISH DIALECT OF SULAIMANIA, THE LANGUAGE OF OFFICIAL PUBLICATIONS AND TEXTBOOKS IN IRAQI KURDISTAN. THE VARIOUS THEMES INCLUDED ARE REPRESENTATIVE OF KURDISH CULTURE AND TRADITION. EACH SELECTION (WRITTEN IN KURDISH SCRIPT) IS FOLLOWED BY VOCABULARY AND EXPLANATORY NOTES IN ORDER OF…

North American Library Education; Directory and Statistics 1971-1973.

ERIC Educational Resources Information Center

Weintraub, D. Kathryn, Ed.; Reed, Sarah R., Ed.

Five separate articles summarize library education at the graduate, undergraduate, and technical assistant levels in the United States and library education in Canada and other parts of North America. Statistical tables are included within the explanatory essays. Over 30 pages of statistical tables give information on specific institutions. The…

Determinants of Crime in Virginia: An Empirical Analysis

ERIC Educational Resources Information Center

Ali, Abdiweli M.; Peek, Willam

2009-01-01

This paper is an empirical analysis of the determinants of crime in Virginia. Over a dozen explanatory variables that current literature suggests as important determinants of crime are collected. The data is from 1970 to 2000. These include economic, fiscal, demographic, political, and social variables. The regression results indicate that crime…

Causal-Explanatory Pluralism: How Intentions, Functions, and Mechanisms Influence Causal Ascriptions

ERIC Educational Resources Information Center

Lombrozo, Tania

2010-01-01

Both philosophers and psychologists have argued for the existence of distinct kinds of explanations, including teleological explanations that cite functions or goals, and mechanistic explanations that cite causal mechanisms. Theories of causation, in contrast, have generally been unitary, with dominant theories focusing either on counterfactual…

Eye Protection in Kansas Schools.

ERIC Educational Resources Information Center

Hay, Kenneth M.; And Others

A law passed by a state legislature requires that students in industrial arts shops and science laboratories must wear eye protective devices. Explanatory material presents the text of the bill and guidelines for implementation, including--(1) types of eye hazards, (2) types of protective devices, (3) administrating eye safety equipment, (4)…

Measurement error in epidemiologic studies of air pollution based on land-use regression models.

PubMed

Basagaña, Xavier; Aguilera, Inmaculada; Rivera, Marcela; Agis, David; Foraster, Maria; Marrugat, Jaume; Elosua, Roberto; Künzli, Nino

2013-10-15

Land-use regression (LUR) models are increasingly used to estimate air pollution exposure in epidemiologic studies. These models use air pollution measurements taken at a small set of locations and modeling based on geographical covariates for which data are available at all study participant locations. The process of LUR model development commonly includes a variable selection procedure. When LUR model predictions are used as explanatory variables in a model for a health outcome, measurement error can lead to bias of the regression coefficients and to inflation of their variance. In previous studies dealing with spatial predictions of air pollution, bias was shown to be small while most of the effect of measurement error was on the variance. In this study, we show that in realistic cases where LUR models are applied to health data, bias in health-effect estimates can be substantial. This bias depends on the number of air pollution measurement sites, the number of available predictors for model selection, and the amount of explainable variability in the true exposure. These results should be taken into account when interpreting health effects from studies that used LUR models.

Statistical Modelling of Temperature and Moisture Uptake of Biochars Exposed to Selected Relative Humidity of Air.

PubMed

Bastistella, Luciane; Rousset, Patrick; Aviz, Antonio; Caldeira-Pires, Armando; Humbert, Gilles; Nogueira, Manoel

2018-02-09

New experimental techniques, as well as modern variants on known methods, have recently been employed to investigate the fundamental reactions underlying the oxidation of biochar. The purpose of this paper was to experimentally and statistically study how the relative humidity of air, mass, and particle size of four biochars influenced the adsorption of water and the increase in temperature. A random factorial design was employed using the intuitive statistical software Xlstat. A simple linear regression model and an analysis of variance with a pairwise comparison were performed. The experimental study was carried out on the wood of Quercus pubescens , Cyclobalanopsis glauca , Trigonostemon huangmosun , and Bambusa vulgaris , and involved five relative humidity conditions (22, 43, 75, 84, and 90%), two mass samples (0.1 and 1 g), and two particle sizes (powder and piece). Two response variables including water adsorption and temperature increase were analyzed and discussed. The temperature did not increase linearly with the adsorption of water. Temperature was modeled by nine explanatory variables, while water adsorption was modeled by eight. Five variables, including factors and their interactions, were found to be common to the two models. Sample mass and relative humidity influenced the two qualitative variables, while particle size and biochar type only influenced the temperature.

[Prediction model of health workforce and beds in county hospitals of Hunan by multiple linear regression].

PubMed

Ling, Ru; Liu, Jiawang

2011-12-01

To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.

Blue and Fin Whale Habitat Modeling from Long-Term Year-Round Passive Acoustic Data from the Southern California Bight

DTIC Science & Technology

2015-09-30

SST), sea surface height anomaly (SSH), chlorophyll a concentration (Chla), and primary productivity (PP). These data are available on similar...between the high and low area, and in areas with low abundance, chlorophyll a concentration was also a significant explanatory variable. For fin

Diagnostic, Explanatory, and Detection Models of Munchausen by Proxy: Extrapolations from Malingering and Deception

ERIC Educational Resources Information Center

Rogers, Richard

2004-01-01

Objective: The overriding objective is a critical examination of Munchausen syndrome by proxy (MSBP) and its closely-related alternative, factitious disorder by proxy (FDBP). Beyond issues of diagnostic validity, assessment methods and potential detection strategies are explored. Methods: A painstaking analysis was conducted of the MSBP and FDBP…

Exogenous and Endogenous Impacts into Teachers' Work Performance Sphere

ERIC Educational Resources Information Center

Nasrun

2016-01-01

By this synopsis research which conveyed of findings to unfold mutual effect between teachers' performance and incentive scheme and teachers' personal competency, and principal leadership, and work motivation, by means of explanatory research in which ex facto method was ad hock model chosen because of classified as non-experiment. The grounds…

An Explanatory Mixed Method Study on Pre-Service Language Teachers' Communication Apprehension towards Their Instructors

ERIC Educational Resources Information Center

Kavanoz, Suzan

2017-01-01

Promoting higher communication efficiency among teacher candidates and acting as models are among the main professional responsibilities of teacher educators. This makes the task of teachers even more important in language education classes where students are prospective language teachers and their development as language teachers highly depend on…

School Climate and Academic Achievement in Suburban Schools

ERIC Educational Resources Information Center

Sulak, Tracey N.

2016-01-01

School climate research has indicated a relationship between the climate of a school and academic achievement. The majority of explanatory models have been developed in urban schools with less attention given to suburban schools. Due to the process of formation of suburban schools, there is a likelihood these campuses differ from the traditional…

Youth Justice in England and Wales: A Risky Business

ERIC Educational Resources Information Center

Paylor, Ian

2011-01-01

Risk factor research dominates explanatory models of youth offending and "evidence-based" policy and practice with young people in the youth justice system in England and Wales. Asset is the product of these actuarial ideas and has put the risk factor prevention paradigm into practice. This article evaluates the impact that an actuarial…

Predicting Middle Level State Standardized Test Results Using Family and Community Demographic Data

ERIC Educational Resources Information Center

Tienken, Christopher H.; Colella, Anthony; Angelillo, Christian; Fox, Meredith; McCahill, Kevin R.; Wolfe, Adam

2017-01-01

The use of standardized test results to drive school administrator evaluations pervades education policymaking in more than 40 states. However, the results of state standardized tests are strongly influenced by non-school factors. The models of best fit (n = 18) from this correlational, explanatory, longitudinal study predicted accurately the…

Diabetes Beliefs among Low-Income, White Residents of a Rural North Carolina Community

ERIC Educational Resources Information Center

Arcury, Thomas A.; Skelly, Anne H.; Gesler, Wilbert M.; Dougherty, Molly C.

2005-01-01

Context: Every social group shares beliefs about health and illness. Knowledge and understanding of these health beliefs are essential for education programs to address health promotion and illness prevention. Purpose: This analysis describes the diabetes Explanatory Models of Illness (EMs) of low-income, rural, white Southerners who have not been…

Does Price Matter? Overseas Students in UK Higher Education

ERIC Educational Resources Information Center

Soo, Kwok Tong; Elliott, Caroline

2010-01-01

This paper explores the determinants of the choice of UK universities by overseas undergraduate applicants. We use data on overseas applicants in Business Studies and Engineering from 2002 to 2007, to 97 UK universities. Estimating using a Hausman-Taylor model to control for the possible correlation between our explanatory variables and…

Economic factors influencing land use changes in the South-Central United States

Treesearch

Ralph J. Alig; Fred C. White; Brian C. Murray

1988-01-01

Econometric models of land use change were estimated for two physiographic regions in the South-Central United States. Results are consistent-with the economic hierarchy of land use, with population and personal income being significant explanatory variables. Findings regarding the importance of relative agricultural and forestry market-based incomes in influencing...

How Robust Is Linear Regression with Dummy Variables?

ERIC Educational Resources Information Center

Blankmeyer, Eric

2006-01-01

Researchers in education and the social sciences make extensive use of linear regression models in which the dependent variable is continuous-valued while the explanatory variables are a combination of continuous-valued regressors and dummy variables. The dummies partition the sample into groups, some of which may contain only a few observations.…

What Does It Mean to Know?

ERIC Educational Resources Information Center

Kirch, Susan A.; Stetsenko, Anna

2012-01-01

What do people mean when they say they "know" something in science? It usually means they did an investigation and expended considerable intellectual effort to build a useful explanatory model. It means they are confident about an explanation, believe others should trust what they say, and believe that their claim is testable. It means they can…

Evaluating Pragmatic Competence in Nigerian Undergraduates' Language Errors within Descriptive ESL Writing

ERIC Educational Resources Information Center

Muhammad, Anas Sa'idu; Nair, Subadrah Madhawa

2017-01-01

This study investigates the level of pragmatic competence for ESL writing skills among Nigerian undergraduates. Methodologically, it adopts descriptive research design within the explanatory framework of the QUAN-Qual model. The instruments used are descriptive essay text and focus group interview questions. In writing the descriptive essays, a…

Exact Interval Estimation, Power Calculation, and Sample Size Determination in Normal Correlation Analysis

ERIC Educational Resources Information Center

Shieh, Gwowen

2006-01-01

This paper considers the problem of analysis of correlation coefficients from a multivariate normal population. A unified theorem is derived for the regression model with normally distributed explanatory variables and the general results are employed to provide useful expressions for the distributions of simple, multiple, and partial-multiple…