835 resultados para Sample losses


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In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier, and we propose an improved estimator of the population frontier. In addition, we provide the exact distribution of the out-of-sample mean and variance of sample minimum-variance portfolios. This allows us to understand the impact of estimation error on the performance of in-sample optimal portfolios. Key Words: minimum-variance frontier; efficiency set constants; finite sample distribution

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Alexithymia is characterised by deficits in emotional insight and self reflection, that impact on the efficacy of psychological treatments. Given the high prevalence of alexithymia in Alcohol Use Disorders, valid assessment tools are critical. The majority of research on the relationship between alexithymia and alcohol-dependence has employed the self-administered Toronto Alexithymia Scale (TAS-20). The Observer Alexithymia Scale (OAS) has also been recommended. The aim of the present study was to assess the validity and reliability of the OAS and the TAS-20 in an alcohol-dependent sample. Two hundred and ten alcohol-dependent participants in an outpatient Cognitive Behavioral Treatment program were administered the TAS-20 at assessment and upon treatment completion at 12 weeks. Clinical psychologists provided observer assessment data for a subsample of 159 patients. The findings confirmed acceptable internal consistency, test-retest reliability and scale homogeneity for both the OAS and TAS-20, except for the low internal consistency of the TAS-20 EOT scale. The TAS-20 was more strongly associated with alcohol problems than the OAS.

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The study described in this paper developed a model of animal movement, which explicitly recognised each individual as the central unit of measure. The model was developed by learning from a real dataset that measured and calculated, for individual cows in a herd, their linear and angular positions and directional and angular speeds. Two learning algorithms were implemented: a Hidden Markov model (HMM) and a long-term prediction algorithm. It is shown that a HMM can be used to describe the animal's movement and state transition behaviour within several “stay” areas where cows remained for long periods. Model parameters were estimated for hidden behaviour states such as relocating, foraging and bedding. For cows’ movement between the “stay” areas a long-term prediction algorithm was implemented. By combining these two algorithms it was possible to develop a successful model, which achieved similar results to the animal behaviour data collected. This modelling methodology could easily be applied to interactions of other animal species.

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Adolescent drinking is a significant issue yet valid psychometric tools designed for this group are scarce. The Drinking Refusal Self-Efficacy Questionnaire—Revised Adolescent Version (DRSEQ-RA) is designed to assess an individual's belief in their ability to resist drinking alcohol. The original DRSEQ-R consists of three factors reflecting social pressure refusal self-efficacy, opportunistic refusal self-efficacy and emotional relief refusal self-efficacy. A large sample of 2020 adolescents aged between 12 and 19 years completed the DRSEQ and measures of alcohol consumption in small groups. Using confirmatory factor analysis, the three factor structure was confirmed. All three factors were negatively correlated with both frequency and volume of alcohol consumption. Drinkers reported lower drinking refusal self-efficacy than non-drinkers. Taken together, these results suggest that the adolescent version of the Drinking Refusal Self-Efficacy Questionnaire (DRSEQ-RA) is a reliable and valid measure of drinking refusal self-efficacy.

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Confirmatory factor analyses were conducted to evaluate the factorial validity of the Toronto Alexithymia Scale in an alcohol-dependent sample. Several factor models were examined, but all models were rejected given their poor fit. A revision of the TAS-20 in alcohol-dependent populations may be needed.

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This study examined the psychometric properties of an expanded version of the Algase Wandering Scale (Version 2) (AWS-V2) in a cross-cultural sample. A cross-sectional survey design was used. Study subjects were 172 English-speaking persons with dementia (PWD) from long-term care facilities in the USA, Canada, and Australia. Two or more facility staff rated each subject on the AWS-V2. Demographic and cognitive data (MMSE) were also obtained. Staff provided information on their own knowledge of the subject and of dementia. Separate factor analyses on data from two samples of raters each explained greater than 66% of the variance in AWS-V2 scores and validated four (persistent walking, navigational deficit, eloping behavior, and shadowing) of five factors in the original scale. Items added to create the AWS-V2 strengthened the shadowing subscale, failed to improve the routinized walking subscale, and added a factor, attention shifting as compared to the original AWS. Evidence for validity was found in significant correlations and ANOVAs between the AWS-V2 and most subscales with a single item indicator of wandering and with the MMSE. Evidence of reliability was shown by internal consistency of the AWS-V2 (0.87, 0.88) and its subscales (range 0.88 to 0.66), with Kappa for individual items (17 of 27 greater than 0.4), and ANOVAs comparing ratings across rater groups (nurses, nurse aids, and other staff). Analyses support validity and reliability of the AWS-V2 overall and for persistent walking, spatial disorientation, and eloping behavior subscales. The AWS-V2 and its subscales are an appropriate way to measure wandering as conceptualized within the Need-driven Dementia-compromised Behavior Model in studies of English-speaking subjects. Suggestions for further strengthening the scale and for extending its use to clinical applications are described.

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Background: Loneliness and low mood are associated with significant negative health outcomes including poor sleep, but the strength of the evidence underlying these associations varies. There is strong evidence that poor sleep quality and low mood are linked, but only emerging evidence that loneliness and poor sleep are associated. Aims: To independently replicate the finding that loneliness and poor subjective sleep quality are associated and to extend past research by investigating lifestyle regularity as a possible mediator of relationships, since lifestyle regularity has been linked to loneliness and poor sleep. Methods: Using a cross-sectional design, 97 adults completed standardized measures of loneliness, lifestyle regularity, subjective sleep quality and mood. Results: Loneliness was a significant predictor of sleep quality. Lifestyle regularity was not a predictor of, nor associated with, mood, sleep quality or loneliness. Conclusions: This study provides an important independent replication of the association between poor sleep and loneliness. However, the mechanism underlying this link remains unclear. A theoretically plausible mechanism for this link, lifestyle regularity, does not explain the relationship between loneliness and poor sleep. The nexus between loneliness and poor sleep is unlikely to be broken by altering the social rhythm of patients who present with poor sleep and loneliness.

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A sample of 815 adults drawn from the general American population provided their perception of the appropriateness of 12 questionable consumer actions in the marketplace. The scenarios investigated ranged from illegal actions such as inflating one’s losses when filing an insurance claim to actions that while not illegal, may raise questions of ethics. The 12 scenarios exhibited a wide range of mean responses on the six-point scale thereby supporting an often stated premise that consumer ethics is situational in nature. An array of commonly employed demographic questions was also included on the Internet-based survey, and differences of opinion were documented across the various demographic segments.

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Research is indicating that individuals who present for DUI treatment may have competing substance abuse and mental health needs. This study aimed to examine the extent of such comorbidity issues among a sample of Texas DUI offenders. Method: Records of 36,372 DUI clients and 308,695 non-DUI clients admitted to Texas treatment programs between 2005 and 2008 were obtained from the State's administrative dataset. The data were analysed to identify the relationship between substance use, psychiatric problems, program completion and recidivism rates. Results: Analysis indicated that while non-DUI clients were more likely to present with more severe illicit substance use problems, DUI clients were more likely to have a primary problem with alcohol. Additionally, a cannabis use problem was also found to be significantly associated with DUI recidivism in the last year. In regards to mental health needs, a major finding was that depression was the most common psychiatric condition reported by DUI clients, including those with more than one DUI offence in the past year. This group were also more at risk of being diagnosed with Bipolar Disorder compared to the general population, and such a diagnosis was also associated with an increased likelihood of not completing treatment. Interestingly, female DUI and non-DUI clients were also more likely to be diagnosed with mental health problems compared to males, as well as more likely to be placed on medications at admission and have problems with methamphetamine, cocaine, and opiates. Conclusion: The findings highlight the complex competing needs of some DUI offenders who enter treatment. The results also suggest that there is a need to utilise mental health and substance abuse screening methods to ensure DUI offenders are directed towards appropriate treatment pathways as well as ensure that such interventions adequately cater for complex substance abuse and psychiatric needs.

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Bicycle injuries, particularly those resulting from single bicycle crashes, are underreported in both police and hospital records. Data on cyclist characteristics and crash circumstances are also often lacking. As a result, the ability to develop comprehensive injury prevention policies is hampered. The aim of this study was to examine the incidence, severity, cyclist characteristics, and crash circumstances associated with cycling injuries in a sample of cyclists in Queensland, Australia. A cross-sectional study of Queensland cyclists was conducted in 2009. Respondents (n=2056) completed an online survey about their cycling experiences, including cycling injuries. Logistic regression modelling was used to examine the associations between demographic and cycling behaviour variables with experiencing cycling injuries in the past year, and, separately, with serious cycling injuries requiring a trip to a hospital. Twenty-seven percent of respondents (n=545) reported injuries, and 6% (n=114) reported serious injuries. In multivariable modelling, reporting an injury was more likely for respondents who had cycled <5 years, compared to ≥10 years (p<0.005); cycled for competition (p=0.01); or experienced harassment from motor vehicle occupants (p<0.001). There were no gender differences in injury incidence, and respondents who cycled for transport did not have an increased risk of injury. Reporting a serious injury was more likely for those whose injury involved other road users (p<0.03). Along with environmental and behavioural approaches for reducing collisions and near-collisions with motor vehicles, interventions that improve the design and maintenance of cycling infrastructure, increase cyclists’ skills, and encourage safe cycling behaviours and bicycle maintenance will also be important for reducing the overall incidence of cycling injuries.