992 resultados para self-estimates


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The purpose of this study was to investigate Howard Gardner's (1983) Multiple Intelligences theory, which proposes that there are eight independent intelligences: Linguistic, Spatial, Logical/Mathematical, Interpersonal, Intrapersonal, Naturalistic, Bodily-Kinesthetic, and Musical. To explore Gardner's theory, two measures of each ability area were administered to 200 participants. Each participant also completed a measure of general cognitive ability, a personality inventory, an ability self-rating scale, and an ability self-report questionnaire. Nonverbal measures were included for most intelligence domains, and a wide range of content was sampled in Gardner's domains. Results showed that all tests of purely cognitive abilities were significantly correlated with the measure of general cognitive ability, whereas Musical, Bodily-Kinesthetic, and one of the Intrapersonal measures were not. Contrary to what Multiple Intelligences theory would seem to predict, correlations among the tests revealed a positive manifold and factor analysis indicated a large factor of general intelligence, with a mathematical reasoning test and a classification task from the Naturalistic domain having the highest ^- loadings. There were only minor sex differences in performance on the ability tests. Participants' self-estimates of ability were significantly and positively correlated with actual performance in some, but not all, intelligences. With regard to personality, a hypothesized association between Openness to Experience and crystallized intelligence was supported. The implications of the findings in regards to the nature of mental abilities were discussed, and recommendations for further research were made.

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Although perceived health risk plays a prominent role in theories of health behavior, its empirical role in risk taking is less clear. In Study 1 (N = 129), 2 measures of drivers' risk-taking behavior were found to be unrelated to self-estimates of accident concern but to be related to self-ratings of driving skill and the perceived thrill of driving. In Study 2 (N = 405), out of a wide range of potential influences, accident concern had the weakest relationship with risk taking. The authors concluded that although health risk is a key feature in many theories of health behavior and a central focus for researchers and policy makers, it may not be such a prominent factor for those actually taking the risk.

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Individuals typically believe that they are less likely than the average person to experience negative events, a phenomenon termed “unrealistic optimism”. The direct method of assessing unrealistic optimism employs a question of the form, “Compared with the average person, what is the chance that X will occur to you?”. However, it has been proposed that responses to such a question (direct-estimates) are based essentially just on estimates that X will occur to the self (self-estimates). If this is so, any factors that affect one of these estimates should also affect the other. This prediction was tested in two experiments. In each, direct- and self-estimates for an unfamiliar health threat—homocysteine-related heart problems—were recorded. It was found that both types of estimate were affected in the same way by varying the stated probability of having unsafe levels of homocysteine (Study 1, N = 149) and varying the stated probability that unsafe levels of homocysteine will lead to heart problems (Study 2, N = 111). The results are consistent with the proposal that direct-estimates are constructed just from self-estimates.

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The direct method of assessing “unrealistic optimism” employs a question of the form, “Compared with the average person, what is the chance that event X will occur to you?” It has been proposed that when individuals construct their responses to this question (direct-estimates) they focus much more strongly on estimates of their own risk (self-estimates) than on estimates of the average person's risk (other-estimates). A challenge to this proposal comes from findings that interventions that alter other-estimates also change direct-estimates. Employing a novel intervention technique, we tested the possibility that such interventions may indirectly also change self-estimates and that this is what accounts for their effect on direct-estimates. Study 1 (n = 58) showed that an intervention which was designed to (and did) affect other-estimates also affected self-estimates, while Study 2 (n = 101) showed that it affected direct-estimates. Study 3 (n = 79) confirmed that we could modify the intervention so as to maintain the effect on other-estimates, but eliminate that on self-estimates. Study 4 (n = 112) demonstrated that when this was done, there was no longer any effect on direct-estimates. The findings are consistent with the proposal that direct-estimates are constructed largely just out of self-estimates. Implications for heath education programs are discussed.

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Although perceived health risk plays a prominent role in theories of health behavior. its empirical role in risk taking is less clear. In Study 1 (N = 129), 2 measures of drivers' risk-taking behavior were found to be unrelated to self-estimates of accident concern but to be related to self-ratings of driving skill and the perceived thrill of driving. In Study 2 (N = 405), out of a wide range of potential influences, accident concern had the weakest relationship with risk taking. The authors concluded that although health risk is a key feature in many theories of health behavior and a central focus for researchers and policy makers, it may not be such a prominent factor for those actually taking the risk.

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In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm-level yield gains from GM crop adoption. Yet most farm-level studies in the literature do not control for farmer self-selection, a potentially important source of bias in such estimates. We use farm-level panel data from Indian cotton farmers to investigate the yield effect of GM insect-resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self-selection. A production function is estimated using a fixed-effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross-sectional estimates of the yield effect of Bt cotton, which do not control for self-selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.

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In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm-level yield gains from GM crop adoption. Yet most farm-level studies in the literature do not control for farmer self-selection, a potentially important source of bias in such estimates. We use farm-level panel data from Indian cotton farmers to investigate the yield effect of GM insect-resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self-selection. A production function is estimated using a fixed-effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross-sectional estimates of the yield effect of Bt cotton, which do not control for self-selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.

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A routine activity for a sports dietitian is to estimate energy and nutrient intake from an athlete's self-reported food intake. Decisions made by the dietitian when coding a food record are a source of variability in the data. The aim of the present study was to determine the variability in estimation of the daily energy and key nutrient intakes of elite athletes, when experienced coders analyzed the same food record using the same database and software package. Seven-day food records from a dietary survey of athletes in the 1996 Australian Olympic team were randomly selected to provide 13 sets of records, each set representing the self-reported food intake of an endurance, team, weight restricted, and sprint/power athlete. Each set was coded by 3-5 members of Sports Dietitians Australia, making a total of 52 athletes, 53 dietitians, and 1456 athlete-days of data. We estimated within- and between- athlete and dietitian variances for each dietary nutrient using mixed modeling, and we combined the variances to express variability as a coefficient of variation (typical variation as a percent of the mean). Variability in the mean of 7-day estimates of a nutrient was 2- to 3-fold less than that of a single day. The variability contributed by the coder was less than the true athlete variability for a 1-day record but was of similar magnitude for a 7-day record. The most variable nutrients (e.g., vitamin C, vitamin A, cholesterol) had approximately 3-fold more variability than least variable nutrients (e.g., energy, carbohydrate, magnesium). These athlete and coder variabilities need to be taken into account in dietary assessment of athletes for counseling and research.

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Immigration has played an important role in the historical development of Australia. Thus, it is no surprise that a large body of empirical work has developed, which focuses upon how migrants fare in the land of opportunity. Much of the literature is comparatively recent, i.e. the last ten years or so, encouraged by the advent of public availability of Australian crosssection micro data. Several different aspects of migrant welfare have been addressed, with major emphasis being placed upon earnings and unemployment experience. For recent examples see Haig (1980), Stromback (1984), Chiswick and Miller (1985), Tran-Nam and Nevile (1988) and Beggs and Chapman (1988). The present paper contributes to the literature by providing additional empirical evidence on the native/migrant earnings differential. The data utilised are from the rather neglected Australian Bureau of Statistics, ABS Special Supplementary Survey No.4. 1982, otherwise known as the Family Survey. The paper also examines the importance of distinguishing between the wage and salary sector and the self-employment sector when discussing native/migrant differentials. Separate earnings equations for the two labour market groups are estimated and the native/migrant earnings differential is broken down by employment status. This is a novel application in the Australian context and provides some insight into the earnings of the selfemployed, a group that despite its size (around 20 per cent of the labour force) is frequently ignored by economic research. Most previous empirical research fails to examine the effect of employment status on earnings. Stromback (1984) includes a dummy variable representing self-employment status in an earnings equation estimated over a pooled sample of paid and self-employed workers. The variable is found to be highly significant, which leads Stromback to question the efficacy of including the self-employed in the estimation sample. The suggestion is that part of self-employed earnings represent a return to non-human capital investment, i.e. investments in machinery, buildings etc, the structural determinants of earnings differ significantly from those for paid employees. Tran-Nam and Nevile (1988) deal with differences between paid employees and the selfemployed by deleting the latter from their sample. However, deleting the self-employed from the estimation sample may lead to bias in the OLS estimation method (see Heckman 1979). The desirable properties of OLS are dependent upon estimation on a random sample. Thus, the 'Ran-Nam and Nevile results are likely to suffer from bias unless individuals are randomly allocated between self-employment and paid employment. The current analysis extends Tran-Nam and Nevile (1988) by explicitly treating the choice of paid employment versus self-employment as being endogenously determined. This allows an explicit test for the appropriateness of deleting self-employed workers from the sample. Earnings equations that are corrected for sample selection are estimated for both natives and migrants in the paid employee sector. The Heckman (1979) two-step estimator is employed. The paper is divided into five major sections. The next section presents the econometric model incorporating the specification of the earnings generating process together with an explicit model determining an individual's employment status. In Section 111 the data are described. Section IV draws together the main econometric results of the paper. First, the probit estimates of the labour market status equation are documented. This is followed by presentation and discussion of the Heckman two-stage estimates of the earnings specification for both native and migrant Australians. Separate earnings equations are estimated for paid employees and the self-employed. Section V documents estimates of the nativelmigrant earnings differential for both categories of employees. To aid comparison with earlier work, the Oaxaca decomposition of the earnings differential for paid-employees is carried out for both the simple OLS regression results as well as the parameter estimates corrected for sample selection effects. These differentials are interpreted and compared with previous Australian findings. A short section concludes the paper.

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This study used data from Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) to investigate how parent report of children’s emotional and cognitive regulation at age 2-3 years was associated with teacher ratings of children’s prosocial behaviors in the early years of school. A sample of 2,392 children was drawn from the LSAC Birth Cohort for the analyses. The analyses used structural equation modeling to estimate parameters of the relationships between key variables. Within the model, estimates of mother-reported emotional and cognitive regulation at age 2 to 3 years were significantly associated with teacher-reported prosocial behavior at 6 to 7 years. Emotional regulation was a slightly stronger indicator of prosocial behavior than cognitive regulation. Being female and from a family with a higher socioeconomic position were also associated with higher levels of prosocial behavior. Results are discussed in relation to the role of early childhood teachers in fostering children’s self-regulatory behaviors and in providing environments in which empathic and prosocial behaviors are modeled, guided, and scaffolded so that foundations are laid for caring behaviors to be understood and internalized by children.

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A "self-exciting" market is one in which the probability of observing a crash increases in response to the occurrence of a crash. It essentially describes cases where the initial crash serves to weaken the system to some extent, making subsequent crashes more likely. This thesis investigates if equity markets possess this property. A self-exciting extension of the well-known jump-based Bates (1996) model is used as the workhorse model for this thesis, and a particle-filtering algorithm is used to facilitate estimation by means of maximum likelihood. The estimation method is developed so that option prices are easily included in the dataset, leading to higher quality estimates. Equilibrium arguments are used to price the risks associated with the time-varying crash probability, and in turn to motivate a risk-neutral system for use in option pricing. The option pricing function for the model is obtained via the application of widely-used Fourier techniques. An application to S&P500 index returns and a panel of S&P500 index option prices reveals evidence of self excitation.

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A predictive model of terrorist activity is developed by examining the daily number of terrorist attacks in Indonesia from 1994 through 2007. The dynamic model employs a shot noise process to explain the self-exciting nature of the terrorist activities. This estimates the probability of future attacks as a function of the times since the past attacks. In addition, the excess of nonattack days coupled with the presence of multiple coordinated attacks on the same day compelled the use of hurdle models to jointly model the probability of an attack day and corresponding number of attacks. A power law distribution with a shot noise driven parameter best modeled the number of attacks on an attack day. Interpretation of the model parameters is discussed and predictive performance of the models is evaluated.

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Background Accelerometers have become one of the most common methods of measuring physical activity (PA). Thus, validity of accelerometer data reduction approaches remains an important research area. Yet, few studies directly compare data reduction approaches and other PA measures in free-living samples. Objective To compare PA estimates provided by 3 accelerometer data reduction approaches, steps, and 2 self-reported estimates: Crouter's 2-regression model, Crouter's refined 2-regression model, the weighted cut-point method adopted in the National Health and Nutrition Examination Survey (NHANES; 2003-2004 and 2005-2006 cycles), steps, IPAQ, and 7-day PA recall. Methods A worksite sample (N = 87) completed online-surveys and wore ActiGraph GT1M accelerometers and pedometers (SW-200) during waking hours for 7 consecutive days. Daily time spent in sedentary, light, moderate, and vigorous intensity activity and percentage of participants meeting PA recommendations were calculated and compared. Results Crouter's 2-regression (161.8 +/- 52.3 minutes/day) and refined 2-regression (137.6 +/- 40.3 minutes/day) models provided significantly higher estimates of moderate and vigorous PA and proportions of those meeting PA recommendations (91% and 92%, respectively) as compared with the NHANES weighted cut-point method (39.5 +/- 20.2 minutes/day, 18%). Differences between other measures were also significant. Conclusions When comparing 3 accelerometer cut-point methods, steps, and self-report measures, estimates of PA participation vary substantially.

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The self-modulation process of a high-frequency surface wave (SW) in a wave-guiding structure - a semibounded magnetoactive plasma and perfectly conducting metal wall - is considered for the weak nonlinearity approximation. Estimates are given for the contributions to the nonlinear frequency shift of the SW from the two principal self-action channels: via the generation of a signal of the doubled frequency and of static surface perturbations, arising as the result of the action of a ponderomotive force. Solutions for the field envelope of the nonlinear wave are examined with regard to their stability with respect to longitudinal and transverse perturbations.

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Objectives: Few studies have assessed the risk and impact of lymphedema among women treated for endometrial cancer. We aimed to quantify cumulative incidence of, and risk factors for developing lymphedema following treatment for endometrial cancer and estimate absolute risk for individuals. Further, we report unmet needs for help with lymphedema-specific issues. Methods: Women treated for endometrial cancer (n = 1243) were followed-up 3–5 years after diagnosis; a subset of 643 completed a follow-up survey that asked about lymphedema and lymphedema-related support needs. We identified a diagnosis of secondary lymphedema from medical records or self-report. Multivariable logistic regression was used to evaluate risk factors and estimates. Results: Overall, 13% of women developed lymphedema. Risk varied markedly with the number of lymph nodes removed and, to a lesser extent, receipt of adjuvant radiation or chemotherapy treatment, and use of nonsteroidal anti-inflammatory drugs (pre-diagnosis). The absolute risk of developing lymphedema was > 50% for women with 15 + nodes removed and 2–3 additional risk factors, 30–41% for those with 15 + nodes removed plus 0–1 risk factors or 6–14 nodes removed plus 3 risk factors, but ≤ 8% for women with no nodes removed or 1–5 nodes but no additional risk factors. Over half (55%) of those who developed lymphedema reported unmet need(s), particularly with lymphedema-related costs and pain. Conclusion: Lymphedema is common; experienced by one in eight women following endometrial cancer. Women who have undergone lymphadenectomy have very high risks of lymphedema and should be informed how to self-monitor for symptoms. Affected women need greater levels of support.