Response Shift and Glycemic Control in Children With Diabetes.

BACKGROUND: The purpose of this study was to investigate the scale recalibration construct of response shift and its relationship to glycemic control in children with diabetes. METHODS: At year 1, thirty-eight children with type 1 diabetes attending a diabetes summer camp participated. At baseline and post-camp they completed the Problem Areas in Diabetes (PAID) questionnaire. Post-camp, the PAID was also completed using the 'thentest' method, which requires a retrospective judgment about their baseline functioning. At year 2, fifteen of the original participants reported their HbA1c. RESULTS: PAID scores significantly decreased from baseline to post-camp. An even larger difference was found between thentest and post-camp scores, suggesting scale recalibration. There was a significant positive correlation between year 1 HbA1c and thentest scores. Partial correlation analysis between PAID thentest scores and year 2 HbA1c, controlling for year 1 HbA1c, showed that higher PAID thentest scores were associated with higher year 2 HbA1c. CONCLUSION: Results from this small sample suggest that children with diabetes do show scale recalibration, and that it may be related to glycemic control.

Empirical Analysis of Credit Risk Regime Switching and Temporal Conditional Default Correlation in Credit Default Swap Valuation: The Market liquidity effect

In this paper, we extend the debate concerning Credit Default Swap valuation to include time varying correlation and co-variances. Traditional multi-variate techniques treat the correlations between covariates as constant over time; however, this view is not supported by the data. Secondly, since financial data does not follow a normal distribution because of its heavy tails, modeling the data using a Generalized Linear model (GLM) incorporating copulas emerge as a more robust technique over traditional approaches. This paper also includes an empirical analysis of the regime switching dynamics of credit risk in the presence of liquidity by following the general practice of assuming that credit and market risk follow a Markov process. The study was based on Credit Default Swap data obtained from Bloomberg that spanned the period January 1st 2004 to August 08th 2006. The empirical examination of the regime switching tendencies provided quantitative support to the anecdotal view that liquidity decreases as credit quality deteriorates. The analysis also examined the joint probability distribution of the credit risk determinants across credit quality through the use of a copula function which disaggregates the behavior embedded in the marginal gamma distributions, so as to isolate the level of dependence which is captured in the copula function. The results suggest that the time varying joint correlation matrix performed far superior as compared to the constant correlation matrix; the centerpiece of linear regression models.