5 resultados para Prediction model
em Brock University, Canada
Resumo:
The study aim was to investigate the relationship between factors related to personal cancer history and lung cancer risk as well as assess their predictive utility. Characteristics of interest included the number, anatomical site(s), and age of onset of previous cancer(s). Data from the Prostate, Lung, Colorectal and Ovarian Screening (PLCO) Cancer Screening Trial (N = 154,901) and National Lung Screening Trial (N = 53,452) were analysed. Logistic regression models were used to assess the relationships between each variable of interest and 6-year lung cancer risk. Predictive utility was assessed through changes in area-under-the-curve (AUC) after substitution into the PLCOall2014 lung cancer risk prediction model. Previous lung, uterine and oral cancers were strongly and significantly associated with elevated 6-year lung cancer risk after controlling for confounders. None of these refined measures of personal cancer history offered more predictive utility than the simple (yes/no) measure already included in the PLCOall2014 model.
Resumo:
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.
Resumo:
years 8 months) and 24 older (M == 7 years 4 months) children. A Monitoring Process Model (MPM) was developed and tested in order to ascertain at which component process ofthe MPM age differences would emerge. The MPM had four components: (1) assessment; (2) evaluation; (3) planning; and (4) behavioural control. The MPM was assessed directly using a referential communication task in which the children were asked to make a series of five Lego buildings (a baseline condition and one building for each MPM component). Children listened to instructions from one experimenter while a second experimenter in the room (a confederate) intetjected varying levels ofverbal feedback in order to assist the children and control the component ofthe MPM. This design allowed us to determine at which "stage" ofprocessing children would most likely have difficulty monitoring themselves in this social-cognitive task. Developmental differences were obselVed for the evaluation, planning and behavioural control components suggesting that older children were able to be more successful with the more explicit metacomponents. Interestingly, however, there was no age difference in terms ofLego task success in the baseline condition suggesting that without the intelVention ofthe confederate younger children monitored the task about as well as older children. This pattern ofresults indicates that the younger children were disrupted by the feedback rather than helped. On the other hand, the older children were able to incorporate the feedback offered by the confederate into a plan ofaction. Another aim ofthis study was to assess similar processing components to those investigated by the MPM Lego task in a more naturalistic observation. Together the use ofthe Lego Task ( a social cognitive task) and the naturalistic social interaction allowed for the appraisal of cross-domain continuities and discontinuities in monitoring behaviours. In this vein, analyses were undertaken in order to ascertain whether or not successful performance in the MPM Lego Task would predict cross-domain competence in the more naturalistic social interchange. Indeed, success in the two latter components ofthe MPM (planning and behavioural control) was related to overall competence in the naturalistic task. However, this cross-domain prediction was not evident for all levels ofthe naturalistic interchange suggesting that the nature ofthe feedback a child receives is an important determinant ofresponse competency. Individual difference measures reflecting the children's general cognitive capacity (Working Memory and Digit Span) and verbal ability (vocabulary) were also taken in an effort to account for more variance in the prediction oftask success. However, these individual difference measures did not serve to enhance the prediction oftask performance in either the Lego Task or the naturalistic task. Similarly, parental responses to questionnaires pertaining to their child's temperament and social experience also failed to increase prediction oftask performance. On-line measures ofthe children's engagement, positive affect and anxiety also failed to predict competence ratings.
Resumo:
This thesis describes an ancillary project to the Early Diagnosis of Mesothelioma and Lung Cancer in Prior Asbestos Workers study and was conducted to determine the effects of asbestos exposure, pulmonary function and cigarette smoking in the prediction of pulmonary fibrosis. 613 workers who were occupationally exposed to asbestos for an average of 25.9 (SD=14.69) years were sampled from Sarnia, Ontario. A structured questionnaire was administered during a face-to-face interview along with a low-dose computed tomography (LDCT) of the thorax. Of them, 65 workers (10.7%, 95%CI 8.12—12.24) had LDCT-detected pulmonary fibrosis. The model predicting fibrosis included the variables age, smoking (dichotomized), post FVC % splines and post- FEV1% splines. This model had a receiver operator characteristic area under the curve of 0.738. The calibration of the model was evaluated with R statistical program and the bootstrap optimism-corrected calibration slope was 0.692. Thus, our model demonstrated moderate predictive performance.
Resumo:
The Feedback-Related Negativity (FRN) is thought to reflect the dopaminergic prediction error signal from the subcortical areas to the ACC (i.e., a bottom-up signal). Two studies were conducted in order to test a new model of FRN generation, which includes direct modulating influences of medial PFC (i.e., top-down signals) on the ACC at the time of the FRN. Study 1 examined the effects of one’s sense of control (top-down) and of informative cues (bottom-up) on the FRN measures. In Study 2, sense of control and instruction-based (top-down) and probability-based expectations (bottom-up) were manipulated to test the proposed model. The results suggest that any influences of medial PFC on the activity of the ACC that occur in the context of incentive tasks are not direct. The FRN was shown to be sensitive to salient stimulus characteristics. The results of this dissertation partially support the reinforcement learning theory, in that the FRN is a marker for prediction error signal from subcortical areas. However, the pattern of results outlined here suggests that prediction errors are based on salient stimulus characteristics and are not reward specific. A second goal of this dissertation was to examine whether ACC activity, measured through the FRN, is altered in individuals at-risk for problem-gambling behaviour (PG). Individuals in this group were more sensitive to the valence of the outcome in a gambling task compared to not at-risk individuals, suggesting that gambling contexts increase the sensitivity of the reward system to valence of the outcome in individuals at risk for PG. Furthermore, at-risk participants showed an increased sensitivity to reward characteristics and a decreased response to loss outcomes. This contrasts with those not at risk whose FRNs were sensitive to losses. As the results did not replicate previous research showing attenuated FRNs in pathological gamblers, it is likely that the size and time of the FRN does not change gradually with increasing risk of maladaptive behaviour. Instead, changes in ACC activity reflected by the FRN in general can be observed only after behaviour becomes clinically maladaptive or through comparison between different types of gain/loss outcomes.