73 resultados para Dynamic data analysis


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Faunal atlases are landscape-level survey collections that can be used for describing spatial and temporal patterns of distribution and densities. They can also serve as a basis for quantitative analysis of factors that may influence the distributions of species. We used a subset of Birds Australia’s Atlas of Australian Birds data (January 1998 to December 2002) to examine the spatio-temporal distribution patterns of 280 selected species in eastern Australia (17–37°S and 136–152°E). Using geographical information systems, this dataset was converted into point coverage and overlaid with a vegetation polygon layer and a half-degree grid. The exploratory data analysis involved calculating species-specific reporting rates spatially, per grid and per vegetation unit, and also temporally, by month and year. We found high spatio-temporal variability in the sampling effort. Using generalised linear models on unaggregated point data, the influences of four factors – survey method and month, geographical location and habitat type – were analysed for each species. When counts of point data were attributed to grid-cells, the total number of species correlated with the total number of surveys, while the number of records per species was highly variable. Surveys had high interannual location fidelity. The predictive values of each of the four factors were species-dependent. Location and habitat were correlated and highly predictive for species with restricted distribution and strong habitat preference. Month was only of importance for migratory species. The proportion of incidental sightings was important for extremely common or extremely rare species. In conclusion, behaviour of species differed sufficiently to require building a customized model for each species to predict distribution. Simple models were effective for habitat specialists with restricted ranges, but for generalists with wide distributions even complex models gave poor predictions.

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Conventional methods of qualitative data analysis require transcription of audio-recorded data prior to conduct of the coding and analysis process. In this paper Alison Hutchinson describes and illustrates an innovative method of data analysis that comprises the use of audio-editing software to save selected audio bytes from digital audio recordings of meetings. The use of a database to code and manage the linked audio files and generate detailed and summary reports, including reporting of code frequencies according to participant code and/or meeting, is also highlighted. The advantage of using this approach in the analysis of audio-recorded data is that the process may be undertaken in the medium in which the data were collected. Though time-consuming, this process negates the need for expensive and time intensive transcription of recorded data.

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This paper proposes to apply multiagent based data mining technologies to biological data analysis. The rationale is justified from multiple perspectives with an emphasis on biological context. Followed by that, an initial multiagent based bio-data mining framework is presented. Based on the framework, we developed a prototype system to demonstrate how it helps the biologists to perform a comprehensive mining task for answering biological questions. The system offers a new way to reuse biological datasets and available data mining algorithms with ease.

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This paper investigates undergraduate programs in electrical and electronics engineering offered by twelve universities in Australia, Asia, Europe, and America. The investigation focuses on the structure and content of the programs, and the contact hour and assessment of the subjects involved in the programs. The investigation is carried out in four stages: selection of universities, collection of data, analysis of data, and formulation of outcomes. A list of subjects is created based on the content of the programs. The average percentage coverage of each subject in the twelve programs is calculated. The subjects are then grouped into nine program components. The average percentage coverage of each component per university is calculated. For each component, the total number of contact hours for lecture, tutorial, and practical is calculated. Also, the average percentage of four assessment methods for each component is found. Discussions on the outcome of the investigation are presented.

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Objective: The pharmacokinetic profile of a drug often gives little indication of its potential therapeutic application, with many therapeutic uses of drugs being discovered serendipitously while being studied for different indications. As hypothesis-driven, quantitative research methodology is exclusively used in early-phase trials, unexpected but important phenomena may escape detection. In this context, this study aimed to examine the potential for integrating qualitative research methods with quantitative methods in early-phase drug trials. To our knowledge, this mixed methodology has not previously been applied to blinded psychopharmacologic trials.

Method: We undertook qualitative data analysis of clinical observations on the dataset of a randomized, double-blind, placebo-controlled trial of N-acetylcysteine (NAC) in patients with DSM-IV-TR–diagnosed schizophrenia (N = 140). Textual data on all participants, deliberately collected for this purpose, were coded using NVivo 2, and emergent themes were analyzed in a blinded manner in the NAC and placebo groups. The trial was conducted from November 2002 to July 2005.

Results: The principal findings of the published trial could be replicated using a qualitative methodology. In addition, significant differences between NAC- and placebo-treated participants emerged for positive and affective symptoms, which had not been captured by the rating scales utilized in the quantitative trial. Qualitative data in this study subsequently led to a positive trial of NAC in bipolar disorder.

Conclusions: The use of qualitative methods may yield broader data and has the potential to complement traditional quantitative methods and detect unexpected efficacy and safety signals, thereby maximizing the findings of early-phase clinical trial research.

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Business analytics has the potential to deliver performance gains and competitive advantage. However, a theoretically grounded model identifying the factors and processes involved in realizing those performance gains has not been clearly articulated in the literature. This paper draws on the literature on dynamic capabilities to develop such a theoretical framework. It identifies the critical roles of organizational routines and organization-wide capabilities for identifying, resourcing and implementing business analytics-based competitive actions in delivering performance gains and competitive advantage. A theoretical framework and propositions for future research are developed.

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From data generated using 1H NMR titrations, different methodologies to calculate binding constants are compared. The ‘local’ analysis method that uses only a single isotherm (only one H-bond donor) is compared against the ‘global’ method (that includes many or all H-bond donors). The results indicate that for simple systems both methods are suitable, however, the global approach consistently provides a K a value with uncertainties up to 30% smaller. For more complex binding, the global analysis method gives much more robust results than the local methods. This study also highlights the need to explore several different modes when data do not fit well to a simple 1:1 complexation model and illustrates the need for better methods to estimate uncertainties in supramolecular binding experiments.

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The dramatic rise in childhood obesity prevalence in the last two decades has prompted concern about the risk factors that may precipitate or maintain weight gain, or both, in early childhood. Media use has long been implicated in policy debates in Australia, particularly around limits to advertising. However the Australian research funding ecology and dominant paradigms in Australian communication and media studies have resulted in a lack of independent, nationally representative studies upon which to base advice. Australian researchers often can’t afford to collect the kind of data they would like in order to intervene productively as policy actors. As a test case for innovative ways round this dilemma, this paper mobilises secondary data analysis methodologies to explore potential influences of parenting on children’s media use and their weight status.

The research reported here uses data from the first three waves of the Longitudinal Study of Australian Children. Results from a path model suggest that children of mothers who were less consistent in the way in which they enforce their rules were more likely to adopt unhealthy lifestyle behaviours, such as sedentary behaviour and consuming unhealthy snacks. Of the lifestyle behaviours considered, time spent watching television or DVDs was the only predictor of child weight status in late childhood. These results suggest a clear pathway linking consistent parenting and other parental practices, children’s lifestyle behaviours and weight status.

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This paper describes the application of existing and novel adaptations of visualisation techniques to routinely collected health data. The aim of this case study is to examine the capacity for visualisation approaches to quickly and e ectively inform clinical, policy, and scal decision making to improve healthcare provision. We demonstrate the use of interactive graphics, fluctuation plots, mosaic plots, time plots, heatmaps, and disease maps to visualise patient admission, transfer, in-hospital mortality, morbidity coding, execution of diagnosis and treatment guidelines, and the temporal and spatial variations of diseases. The relative e ectiveness of these techniques and associated challenges are discussed.

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This small-scale study carried out in a Melbourne metropolitan hospital explored patients’ and their carers’ perceptions of information, adequacy of information, and their utilization of information concerning post-discharge care received from health professionals during their stay in hospital. The research design consisted of two stages. Stage one involved a qualitative approach using focused interviews of five pairs of patients and their carers, 2 weeks after discharge from hospital. Five main themes emerged from the content analysis of the interview transcripts: information given by health professionals to patients and carers, patients’ and carers’ psychological well-being, activities of daily living, caring tasks of the patients, and community linkages. A quantitative approach was used for stage two involving two sets of questionnaires, one for the patient and one for the carer, developed from the themes identified in stage one. A pilot study was conducted on three pairs of patients and their carers, 2 weeks after discharge from hospital. The main study consisted of a convenience sample of 40 pairs of patients and their carers who completed the questionnaires 2 weeks post-discharge. Data analysis of stage two of the study consisted of descriptive statistics and cross-tabulations. The main findings suggested that carers received very little information from health professionals concerning their patients’ health problems and care at home. The carers’ health and employment states were often not considered in their patients’ discharge plan. Carers who were present with their patients when they received information concerning post-discharge care experienced a decrease in anxiety during their patients’ convalescence at home, greater satisfaction with the information they received, and their patients experienced fewer medical problems post-discharge. The implications for nursing practice and research include recommendations for a more effective system of discharge planning, and further research to include a larger population with a more varied group of participants.

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Background
Intervention research provides important information regarding feasible and effective interventions for health policy makers, but few empirical studies have explored the mechanisms by which these studies influence policy and practice. This study provides an exploratory case series analysis of the policy, practice and other related impacts of the 15 research projects funded through the New South Wales Health Promotion Demonstration Research Grants Scheme during the period 2000 to 2006, and explored the factors mediating impacts.

Methods

Data collection included semi-structured interviews with the chief investigators (n = 17) and end-users (n = 29) of each of the 15 projects to explore if, how and under what circumstances the findings had been used, as well as bibliometric analysis and verification using documentary evidence. Data analysis involved thematic coding of interview data and triangulation with other data sources to produce case summaries of impacts for each project. Case summaries were then individually assessed against four impact criteria and discussed at a verification panel meeting where final group assessments of the impact of research projects were made and key influences of research impact identified.

Results
Funded projects had variable impacts on policy and practice. Project findings were used for agenda setting (raising awareness of issues), identifying areas and target groups for interventions, informing new policies, and supporting and justifying existing policies and programs across sectors. Reported factors influencing the use of findings were: i) nature of the intervention; ii) leadership and champions; iii) research quality; iv) effective partnerships; v) dissemination strategies used; and, vi) contextual factors.

Conclusions
The case series analysis provides new insights into how and under what circumstances intervention research is used to influence real world policy and practice. The findings highlight that intervention research projects can achieve the greatest policy and practice impacts if they address proximal needs of the policy context by engaging end-users from the inception of projects and utilizing existing policy networks and structures, and using a range of strategies to disseminate findings that go beond traditional peer review publications.

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The calculation of the first few moments of elution peaks is necessary to determine: the amount of component in the sample (peak area or zeroth moment), the retention factor (first moment), and the column efficiency (second moment). It is a time consuming and tedious task for the analyst to perform these calculations, thus data analysis is generally completed by data stations associated to modern chromatographs. However, data acquisition software is a black box which provides no information to chromatographers on how their data are treated. These results are too important to be accepted on blind faith. The location of the peak integration boundaries is most important. In this manuscript, we explore the relationships between the size of the integration area, the relative position of the peak maximum within this area, and the accuracy of the calculated moments. We found that relationships between these parameters do exist and that computers can be programmed with relatively simple routines to automatize the extraction of key peak parameters and to select acceptable integration boundaries. It was also found that the most accurate results are obtained when the S/N exceeds 200.

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As part of a longitudinal study, infant/toddler pretend play development and maternal play modelling were investigated in dyadic context. A total of 21 children were videotaped in monthly play sessions with their mothers, from age 8 to 17 months. Child and mother pretend play frequencies and levels were measured using Brown’s Pretend Play Observation Scale. Child IQ assessments at 5 years (Stanford–Binet IV) indicated average to high ability levels (M = 122.62). Descriptive analyses showed that children’s levels of pretend development were markedly in advance of age-typical expectations. With a previous analysis showing no specific associations between play levels and IQ, intensive maternal scaffolding, data analysis approaches and use of abstract play materials are proposed as possible contributory factors to the children’s advanced pretend play development.

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Interpretative Phenomenological Analysis (IPA) has developed internationally into a growing qualitative approach to research in the areas of psychology, health sciences, social sciences, education and also specifically in music education. This chapter focuses on IPA as an experiential approach to research which explores the lived experience of the individual’s perception and how individuals make sense of it in their given context. As with other forms of phenomenological research, IPA takes account of the researcher’s own context and perceptions through a process of interpretation, while analyzing the phenomena under study. IPA offers a framework to undertake research based on the traditions of phenomenology, which uncover meanings and hermeneutics which interpret the meaning; it is idiographic in nature when undertaking data analysis. This chapter provides a narrative on IPA as an appropriate methodology that can be used when undertaking research in education and in particularly music education. As a tertiary researcher of music education I have employed IPA in my research. This chapter attempts to address broad questions in relation to: What is IPA? Where does it come from? How is it used? How does one analyze interview data and construct themes? A brief discussion of the strengths and limitations of the method is posed, giving examples where IPA has been successfully employed in music research. By balancing the tensions between phenomenology, hermeneutics and idiographic approaches, IPA situates music and music education research within the realm of qualitative experiential research. I argue that if more music educators apply IPA to their research, we can look forward to the emergence of new insights from research in music and music education that is rigorous and offers both convergent and divergent analysis, beyond description, using interpretation to explain insights.

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Background: Debate is ongoing about what role, if any, variation in the serotonin transporter linked polymorphic region (5-HTTLPR) plays in depression. Some studies report an interaction between 5-HTTLPR variation and stressful life events affecting the risk for depression, others report a main effect of 5-HTTLPR variation on depression, while others find no evidence for either a main or interaction effect. Meta-analyses of multiple studies have also reached differing conclusions.

Methods/Design:
To improve understanding of the combined roles of 5-HTTLPR variation and stress in the development of depression, we are conducting a meta-analysis of multiple independent datasets. This coordinated approach utilizes new analyses performed with centrally-developed, standardized scripts. This publication documents the protocol for this collaborative, consortium-based meta-analysis of 5-HTTLPR variation, stress, and depression.

Study eligibility criteria: Our goal is to invite all datasets, published or unpublished, with 5-HTTLPR genotype and assessments of stress and depression for at least 300 subjects. This inclusive approach is to minimize potential impact from publication bias.

Data sources: This project currently includes investigators from 35 independent groups, providing data on at least N = 33,761 participants.  The analytic plan was determined prior to starting data analysis. Analyses of individual study datasets will be performed by the investigators who collected the data using centrally-developed standardized analysis scripts to ensure a consistent analytical approach across sites. The consortium as a group will review and interpret the meta-analysis results.

Discussion:
Variation in 5-HTTLPR is hypothesized to moderate the response to stress on depression. To test specific hypotheses about the role of 5-HTTLPR variation on depression, we will perform coordinated meta-analyses of de novo results obtained from all available data, using variables and analyses determined a priori. Primary analyses, based on the original 2003 report by Caspi and colleagues of a GxE interaction will be supplemented by secondary analyses to help interpret and clarify issues ranging from the mechanism of effect to heterogeneity among the contributing studies. Publication of this protocol serves to protect this project from biased reporting and to improve the ability of readers to interpret the results of this specific meta-analysis upon its completion.