Cognitive Behavior Therapy for Obsessive-Compulsive Behavior in Children with Autism Spectrum Disorder: A Comparison of Hierarchical Linear Modelling and Visual Analysis

Behavioral researchers commonly use single subject designs to evaluate the effects of a given treatment. Several different methods of data analysis are used, each with their own set of methodological strengths and limitations. Visual inspection is commonly used as a method of analyzing data which assesses the variability, level, and trend both within and between conditions (Cooper, Heron, & Heward, 2007). In an attempt to quantify treatment outcomes, researchers developed two methods for analysing data called Percentage of Non-overlapping Data Points (PND) and Percentage of Data Points Exceeding the Median (PEM). The purpose of the present study is to compare and contrast the use of Hierarchical Linear Modelling (HLM), PND and PEM in single subject research. The present study used 39 behaviours, across 17 participants to compare treatment outcomes of a group cognitive behavioural therapy program, using PND, PEM, and HLM on three response classes of Obsessive Compulsive Behaviour in children with Autism Spectrum Disorder. Findings suggest that PEM and HLM complement each other and both add invaluable information to the overall treatment results. Future research should consider using both PEM and HLM when analysing single subject designs, specifically grouped data with variability.

Linking Ethical Leadership and Employees’ In-Role Performance: Exploring the Mediating Roles of Psychological Capital and Follower-Leader Relational Capital

This study investigates the mediating impact of psychological capital and follower-leader relational capital on the relationship between ethical leadership and in-role performance through the lenses of social exchange theory, social information processing theory, and psychological resources theory. Analysis of data collected from a sample of 171 employees and 24 supervisors from Pakistan reveals that ethical leadership has a positive effect on followers’ in-role job performance, yet this effect is fully explained through the role of psychological capital and partially through follower-leader relational capital. Significant implications of these findings for further research and practice are discussed.

Investigation of the Relationship between Sexual Orientation and Objective Height, along with Predictors of Height Distortion

Studies that have used mostly self-reported height have found that men with a same-sex orientation and women with an other-sex orientation are shorter, on average, than men with an other-sex orientation and women with a same-sex orientation, respectively. This thesis examined whether an objective height difference exists or whether a psychosocial account (e.g., distortion of self-reports) may explain these putative height differences. Also, this thesis examined whether certain individual differences (e.g, gender roles and socially desirable responding) predict height distortion. Eight hundred and thirteen participants, recruited at Brock University, the Niagara Community and through surrounding LGBT events, completed self-reported height, measures of gender roles and socially desirable responding, and had their height measured. Using hierarchical linear regressions, it was found that Same-Sex/Both-Sex Oriented men were shorter, on average, than predominantly Other-Sex Oriented men; however, there was no difference in objective height between Same-Sex/Both-Sex Oriented women and predominantly Other-Sex Oriented women. These findings contribute to existing biological theories of men's sexual orientation development and do not contribute to biological theories of women's sexual orientation development. Height distortion was not related to sexual orientation and only marginally related to sex. Predictors of height distortion were Impression Management, in both men and women, and Unmitigated Agency, in men. These findings highlight the complexity of sexual orientation development in men and women. These findings also highlight the role of certain psychosocial factors in how people perceive their bodies and/or how they want their bodies to be perceived by others.

Using a Bayesian model for bankruptcy prediction : a comparative approach

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.