17 resultados para Gross Rating Points (GRP’s)
em Brock University, Canada
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The relationship between the child's cogni tive development and neurological maturation has been of theoretical interest for many year s. Due to diff iculties such as the lack of sophisticated techniques for measur ing neurolog ical changes and a paucity of normative data, few studies exist that have attempted to correlate the two factors. Recent theory on intellectual development has proposed that neurological maturation may be a factor in the increase of short-term memory storage space. Improved technology has allowed reliable recordings of neurolog ical maturation.. In an attempt to correlate cogni tive development and neurological maturation, this study tested 3-and II-year old children. Fine motor and gross motor short-term memory tests were used to index cogni tive development. Somatosensory evoked potentials elici ted by median nerve stimulation were used to measure the time required for the sensation to pass along the nerve to specific points on the somatosensory pathway. Times were recorded for N14, N20, and P22 interpeak latencies. Maturation of the central nervous system (brain and spinal cord) and the peripheral nervous system (outside the brain and spinal cord) was indi~ated by the recorded times. Signif icant developmental di fferences occurred between 3-and ll-year-olds in memory levels, per ipheral conduction velocity and central conduction times. Linear regression analyses showed that as age increased, memory levels increased and central conduction times decreased. Between the ll-year-old groups, there were no significant differences in central or peripheral nervous system maturation between subjects who achieved a 12 plus score on the digit span test of the WISC-R and those who scored 7 or lower on the same test. Levels achieved on the experimental gross and fine motor short-term memory tests differed significantly within the ll-year-old group.
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Cover title.
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Includes index.
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At head of title: "Great tourist route of America".
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Appendix: On the conduct of the government of United States towards the Indian tribes: p.[129]-139.
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This study sought to compare the results of the Motivation Assessment Scale (MAS; Durand & Crimmins, 1988), Questions About Behavior Function Scale (QABF; Matson & Vollmer, 1996) and Functional Analysis Screening Tool (FAST; Iwata & Deleon, 1996), when completed by parent informants in a sample of children and youth with autism spectrum disorders (ASD) who display challenging behaviour. Results indicated that there was low agreement between the functional hypotheses derived from each of three measures. In addition, correlations between functionally analogous scales were substantially lower than expected, while correlations between non-analogous subscales were stronger than anticipated. As indicated by this study, clinicians choosing to use FBA questionnaires to assess behavioural function, may not obtain accurate functional hypotheses, potentially resulting in ineffective intervention plans. The current study underscores the caution that must be taken when asking parents to complete these questionnaires to determine the function(s) of challenging behaviour for children/youth with ASD.
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The purpose of this study is to examine the impact of the choice of cut-off points, sampling procedures, and the business cycle on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy. To test the impact of the choice of cut-off points and sampling procedures, three bankruptcy prediction models are assessed- Bayesian, Hazard and Mixed Logit. A salient feature of the study is that the analysis includes both parametric and nonparametric bankruptcy prediction models. A sample of firms from Lynn M. LoPucki Bankruptcy Research Database in the U. S. was used to evaluate the relative performance of the three models. The choice of a cut-off point and sampling procedures were found to affect the rankings of the various models. In general, the results indicate that the empirical cut-off point estimated from the training sample resulted in the lowest misclassification costs for all three models. Although the Hazard and Mixed Logit models resulted in lower costs of misclassification in the randomly selected samples, the Mixed Logit model did not perform as well across varying business-cycles. In general, the Hazard model has the highest predictive power. However, the higher predictive power of the Bayesian model, when the ratio of the cost of Type I errors to the cost of Type II errors is high, is relatively consistent across all sampling methods. Such an advantage of the Bayesian model may make it more attractive in the current economic environment. This study extends recent research comparing the performance of bankruptcy prediction models by identifying under what conditions a model performs better. It also allays a range of user groups, including auditors, shareholders, employees, suppliers, rating agencies, and creditors' concerns with respect to assessing failure risk.