Assessment of Blood Glucose and Calcium Concentrations Among healthy female volunteers Blood glucose & calcium in females

Abstract: Hypoglycemia and Hyperglycemia are associated with a number of complications including kidney damage, neurological damage, cardiovascular damage,  damage to the retina or damage to feet and legs,  lethargy, impaired mental functioning and irritability. The most abundant mineral in the body is calcium. Its abnormal levels also associated with multiple disorders. Objectives: The aim of this study was to assess the blood glucose and calcium levels in healthy female volunteersMethods: A cross sectional study was conducted at the Sir Ganga Ram Hospital, Lahore, over a period of 6 months, after obtaining the ethical approval from the The University of Lahore. A total number of 60 females were enrolled through consecutive sampling technique. Females of all age groups were included. All of the females had gone through routine history taking and lab investigations for the assessment of blood glucose an calcium concentrations. Results: In this study out 60 female participants, 33.3% were between ages of 15-30 years, 33.3% were between age of 31-50 years and remaining 33.3% were above 50 years old. All females of age group 15-30 years had normal glucose levels while single case of age group 15-30 years had abnormal calcium level. The results indicated that females of above age 50 years had low calcium and high glucose levels due to poor nutrition and less physical activity. Conclusions: The results of the current study showed that females with increasing age should intake food enriched in calcium and low glucose and adopt a physically active life style to manage normal blood glucose levels.

Influence Analysis of Some Alternatives to Ordinary Least Squares Estimator in Parametric Regression Models

This thesis investigates diagnostic methods in parametric regression models with some alternatives to ordinary least squares estimator. Of which, the Liu estimator has been developed as an alternative to the ordinary least squares estimator in the presence of collinearity among the regressors in linear regression models. Firstly, we presented the DFFITS and different versions of the Cook distance analogous to the ones given for the ordinary linear regression models of each individual observation on the Liu estimates. We suggested a version of the Cook distance based on one-step approximation. The mean shift outlier model for the Liu regression has also been investigated. Moreover, using the Sherman-Morrison-Woodbury theorem, we proposed approximate versions of the DFFITS and the Cook distance. Next, the pseudo likelihood function is given for estimating the regression coefficients and shape parameter as well as to establish local influence diagnostics. The normal curvatures of local influence are deduced under arbitrary perturbation schemes to detect influential observations. Then, we discussed the assessment of local influence under the modified ridge regression with normal error distribution. Using a pseudo-likelihood function, we expressed the normal curvatures of local influence for useful perturbation schemes in interpretable forms.Finally, local influence diagnostic methods in the modified ridge regression are deduced under heavy-tailed error distribution. The methods of analysis we presented have considerable significance for the detection of influential observations in the Liu and the modified ridge regression models. Examples using real-life data sets are used to illustrate the proposed methodology.