960 resultados para multivariate Methoden


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The Driver Behaviour Questionnaire (DBQ) continues to be the most widely utilised self-report scale globally to assess crash risk and aberrant driving behaviours among motorists. However, the scale also attracts criticism regarding its perceived limited ability to accurately identify those most at risk of crash involvement. This study reports on the utilisation of the DBQ to examine the self-reported driving behaviours (and crash outcomes) of drivers in three separate Australian fleet samples (N = 443, N = 3414, & N = 4792), and whether combining the samples increases the tool’s predictive ability. Either on-line or paper versions of the questionnaire were completed by fleet employees in three organisations. Factor analytic techniques identified either three or four factor solutions (in each of the separate studies) and the combined sample produced expected factors of: (a) errors, (b) highway-code violations and (c) aggressive driving violations. Highway code violations (and mean scores) were comparable across the studies. However, across the three samples, multivariate analyses revealed that exposure to the road was the best predictor of crash involvement at work, rather than DBQ constructs. Furthermore, combining the scores to produce a sample of 8649 drivers did not improve the predictive ability of the tool for identifying crashes (e.g., 0.4% correctly identified) or for demerit point loss (0.3%). The paper outlines the major findings of this comparative sample study in regards to utilising self-report measurement tools to identify “at risk” drivers as well as the application of such data to future research endeavours.

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Provenance studies of iron-age pottery specimens originating from the Mngeni river area in South Africa was carried out by applying XRF spectrometry. A total of sixteen major and trace elements were analysed in a batch of 107 potsherds, excavated from four different archaeological sites in the aforementioned area. A multivariate statistical programme Correspondence Analysis was used in this study to obtain the relevant clustering patterns according to the similarity of the elemental distributions. Differences and similarities in the clusters obtained for the majors and trace elements are discussed.

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Objectives: The purpose of this study was to investigate the characteristics associated with fatal and non-fatal low-speed vehicle run-over (LSVRO) events in relation to person, incident and injury characteristics, in order to identify appropriate points for intervention and injury prevention. Methods: Data on all known LSVRO events in Queensland, Australia, over 11 calendar years (1999–2009) were extracted from five different databases representing the continuum of care ( prehospital to fatality) and manually linked. Descriptive and multivariate analyses were used to analyse the sample characteristics in relation to demographics, health service usage, outcomes, incident characteristics, and injury characteristics. Results: Of the 1641 LSVRO incidents, 98.4% (n=1615) were non-fatal, and 1.6% were fatal (n=26). Over half the children required admission to hospital (56%, n=921); mean length of stay was 3.4 days. Younger children aged 0–4 years were more frequently injured, and experienced more serious injuries with worse outcomes. Patterns of injury (injury type and severity), injury characteristics (eg, time of injury, vehicle type, driver of vehicle, incident location), and demographic characteristics (such as socioeconomic status, indigenous status, remoteness), varied according to age group. Almost half (45.6%; n=737) the events occurred outside major cities, and approximately 10% of events involved indigenous children. Parents were most commonly the vehicle drivers in fatal incidents. While larger vehicles such as four-wheel drives (4WD) were most frequently involved in LSVRO events resulting in fatalities, cars were most frequently involved in non-fatal events. Conclusions: This is the first study, to the authors’ knowledge, to analyse the characteristics of fatal and non-fatal LSVRO events in children aged 0–15 years on a state-wide basis. Characteristics of LSVRO events varied with age, thus age-specific interventions are required. Children living outside major cities, and indigenous children, were over-represented in these data. Further research is required to identify the burden of injury in these groups.

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This study developed an understanding of hydrological processes within the Cressbrook Creek catchment of the upper Brisbane River, in particular for the alluvial aquifers. Those aquifers within the lower catchment are used for intensive irrigation, and have been impacted by long-term drought followed by flooding. The study utilised water chemistry, isotopic characters and hydraulic measurements to determine factors such as recharge, links between creeks and groundwater, and variations in water quality. The catchment-wide study will enable improved management of the local water resources.

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In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM–test is derived to test the constancy of correlations and LM- and Wald tests to test the hypothesis of partially constant correlations. Analytical expressions for the test statistics and the required derivatives are provided to make computations feasible. An empirical example based on daily return series of five frequently traded stocks in the S&P 500 stock index completes the paper.

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This research has successfully developed a novel synthetic structural health monitoring system model that is cost-effective and flexible in sensing and data acquisition; and robust in the structural safety evaluation aspect for the purpose of long-term and frequent monitoring of large-scale civil infrastructure during their service lives. Not only did it establish a real-world structural monitoring test-bed right at the heart of QUT Gardens Point Campus but it can also facilitate reliable and prompt protection for any built infrastructure system as well as the user community involved.

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PURPOSE The purpose of this study was to demonstrate the potential of near infrared (NIR) spectroscopy for characterizing the health and degenerative state of articular cartilage based on the components of the Mankin score. METHODS Three models of osteoarthritic degeneration induced in laboratory rats by anterior cruciate ligament (ACL) transection, meniscectomy (MSX), and intra-articular injection of monoiodoacetate (1 mg) (MIA) were used in this study. Degeneration was induced in the right knee joint; each model group consisted of 12 rats (N = 36). After 8 weeks, the animals were euthanized and knee joints were collected. A custom-made diffuse reflectance NIR probe of 5-mm diameter was placed on the tibial and femoral surfaces, and spectral data were acquired from each specimen in the wave number range of 4,000 to 12,500 cm(-1). After spectral data acquisition, the specimens were fixed and safranin O staining (SOS) was performed to assess disease severity based on the Mankin scoring system. Using multivariate statistical analysis, with spectral preprocessing and wavelength selection technique, the spectral data were then correlated to the structural integrity (SI), cellularity (CEL), and matrix staining (SOS) components of the Mankin score for all the samples tested. RESULTS ACL models showed mild cartilage degeneration, MSX models had moderate degeneration, and MIA models showed severe cartilage degenerative changes both morphologically and histologically. Our results reveal significant linear correlations between the NIR absorption spectra and SI (R(2) = 94.78%), CEL (R(2) = 88.03%), and SOS (R(2) = 96.39%) parameters of all samples in the models. In addition, clustering of the samples according to their level of degeneration, with respect to the Mankin components, was also observed. CONCLUSIONS NIR spectroscopic probing of articular cartilage can potentially provide critical information about the health of articular cartilage matrix in early and advanced stages of osteoarthritis (OA). CLINICAL RELEVANCE This rapid nondestructive method can facilitate clinical appraisal of articular cartilage integrity during arthroscopic surgery.

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Structural equation modeling (SEM) is a versatile multivariate statistical technique, and applications have been increasing since its introduction in the 1980s. This paper provides a critical review of 84 articles involving the use of SEM to address construction related problems over the period 1998–2012 including, but not limited to, seven top construction research journals. After conducting a yearly publication trend analysis, it is found that SEM applications have been accelerating over time. However, there are inconsistencies in the various recorded applications and several recurring problems exist. The important issues that need to be considered are examined in research design, model development and model evaluation and are discussed in detail with reference to current applications. A particularly important issue concerns the construct validity. Relevant topics for efficient research design also include longitudinal or cross-sectional studies, mediation and moderation effects, sample size issues and software selection. A guideline framework is provided to help future researchers in construction SEM applications.

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Purpose – The purpose of this paper is to examine the effect of superstars (and other factors) on football fans’ attraction to competition (i.e. disloyal behavior). Design/methodology/approach – A proprietary data set including archival data on professional German football players and clubs as well as survey data of more than 900 football fans is used. The hypotheses are tested with two-sample mean-comparison t-tests and multivariate probit models. Findings – This study provides evidence that superstars both attract new fans and contribute to the retention of existing fans. While the presence of superstars, team loyalty and team identification prevent football fans from being attracted to competition, the team's recent performance seems to have no effect. Fans who select their favorite player from a competing team rather choose superstars, young players, players who are known for exemplary behavior and defenders. Originality/value – This paper contributes to existing research by expanding the list of antecedents of disloyalty and by being the first to employ independent, quantitative data for the assessment of superstar characteristics in the context of team loyalty.

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Introduction: Research that has focused on the ability of self-report assessment tools to predict crash outcomes has proven to be mixed. As a result, researchers are now beginning to explore whether examining culpability of crash involvement can subsequently improve this predictive efficacy. This study reports on the application of the Manchester Driver Behaviour Questionnaire (DBQ) to predict crash involvement among a sample of general Queensland motorists, and in particular, whether including a crash culpability variable improves predictive outcomes. Surveys were completed by 249 general motorists on-line or via a pen-and-paper format. Results: Consistent with previous research, a factor analysis revealed a three factor solution for the DBQ accounting for 40.5% of the overall variance. However, multivariate analysis using the DBQ revealed little predictive ability of the tool to predict crash involvement. Rather, exposure to the road was found to be predictive of crashes. An analysis into culpability revealed 88 participants reported being “at fault” for their most recent crash. Corresponding between and multi-variate analyses that included the culpability variable did not result in an improvement in identifying those involved in crashes. Conclusions: While preliminary, the results suggest that including crash culpability may not necessarily improve predictive outcomes in self-report methodologies, although it is noted the current small sample size may also have had a deleterious effect on this endeavour. This paper also outlines the need for future research (which also includes official crash and offence outcomes) to better understand the actual contribution of self-report assessment tools, and culpability variables, to understanding and improving road safety.

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Purpose: To determine the effect of Type 1 diabetes (DM1) on amplitude of accommodation. Method: There were 43 participants (33 ± 8 years) with DM1 and 32 (34 ± 8 years) age-balanced controls. Amplitude was measured objectively with a COAS wavefront aberrometer and subjectively with a Badal hand optometer. Results: Across both groups, objective amplitude was less than subjective amplitude by 1.4 ± 1.2 D. People with diabetes had lower objective (2.7±1.6 D) and subjective (4.0±1.7 D) amplitudes than people without diabetes (objective 4.1±2.1 D, subjective 5.6±2.1 D). For the DM1 group, the objective and subjective multivariate linear regressions were 7.1 – 0.097Age – 0.076DiabDur (R2 0.51) and 9.1 –0.103Age – 0.106DiabDur (R2 0.63), respectively. Conclusion: Objective and subjective techniques showed lowered amplitude of accommodation in DM1 participants compared with age-matched controls. Loss was affected strongly by duration of diabetes. People with diabetes will experience presbyopia earlier in life than people without diabetes.

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Background and Objectives: Cannabis use is common in early psychosis and has been linked to adverse outcomes. However, factors that influence and maintain change in cannabis use in this population are poorly understood. An existing prospective dataset was used to predict abstinence from cannabis use over the 6 months following inpatient admission for early psychosis. Methods: Participants were 67 inpatients with early psychosis who had used cannabis in the 6 weeks prior to admission. Current diagnoses of psychotic and substance use disorders were confirmed using a clinical checklist and structured diagnostic interview. Measures of clinical, substance use and social and occupational functioning were administered at baseline and at least fortnightly over the 6-month follow up. Results: No substance use or clinical variables were associated with 6-months’ of cannabis abstinence. Only Caucasian ethnicity, living in private accommodation and receiving an income before the admission were predictive. Only private accommodation and receiving an income were significant predictors of abstinence when these variables were entered into a multivariate analysis. Conclusions: While the observed relationships do not necessarily imply causation, they suggest that more optimal substance use outcomes could be achieved by addressing the accommodation and employment needs of patients.

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The echolocation calls of long-tailed bats (Chalinolobus tuberculatus) were recorded in the Eglinton Valley, Fjordland, New Zealand, and digitized for analysis with the signal-processing software. Univariate and multivariate analyses of measure features facilitated a quantitative classification of the calls. Cluster analysis was used to categorize calls into two groups equating to search and terminal buzz calls described qualitatively for other species. When moving from search to terminal phases, the calls decrease in bandwidth, maximum and minimum frequency of call, and duration. Search calls begin with a steep-downward FM sweep followed by a short, less-modulated component. Buzz calls are FM sweeps. Although not found quantitatively, a broad pre-buzz group of calls also was identified. Ambiguity analysis of calls from the three groups shows that search-phrase calls are well suited to resolving the velocity of targets, and hence, identifying moving targets in a stationary clutter. Pre-buzz and buzz calls are better suited to resolving range, a feature that may aid the bats in capture of evasive prey after it has been identified.

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This paper describes the search-phase echolocation calls of lesser short-tailed bats (Mystacina tuberculata) and long-tailed bats (Chalinolobus tuberculatus). Calls were recorded from all three subspecies of short-tailed bat and seven populations of long-tailed bat, three in Northland, two in the central North Island, and two in the lower South Island. The calls were recorded in the field and digitised, then three spectral components and one temporal component of the calls were measured. Calls of the lesser short-tailed bat could be loosely classified into subspecies by means of multivariate discriminant function analysis. Similarly, long-tailed bat calls showed regional variation, and discriminant function analysis was able to fit calls to regional groups with a high rate of success. The significance of the results presented is discussed in terms of the conservation of New Zealand bats and the unique ecology of the lesser short-tailed bat.