D s -optimal designs for Kozak's tree taper model

In this work, we study D _s -optimal design for Kozak's tree taper model. The approximate D _s -optimal designs are found invariant to tree size and hence create a ground to construct a general replication-free D _s -optimal design. Even though the designs are found not to be dependent on the parameter value p of the Kozak's model, they are sensitive to the s×1 subset parameter vector values of the model. The 12 points replication-free design (with 91% efficiency) suggested in this study is believed to reduce cost and time for data collection and more importantly to precisely estimate the subset parameters of interest.     

Adaptation and Dissonance in Quality of Life: A Case Study in Mekelle,Ethiopia

This study aimed to determine predictability of life satisfaction by focusing on social support, substance abuse, socio-demographic factors as well as received health services from medical and traditional centers in the elderly with dementia. The subjects were 1,210 non-institutionalized Malaysian elderly with cognitive problems. In addition, age, ethnicity, sex differences, marital status, educational level, social support, substance abuse and receiving health services were evaluated to predict the risk of falls in samples. Social support was measured by Lubben score. Substance abuse was referred to smoking per day, addiction to alcohol consumption as well as dependency to medications. Health care supports, which were received by individuals included medical and traditional treatments. Life satisfaction was measured by asking in general ‘Are you satisfied with your current life’. The multiple logistic regression analysis was used to determine the effects of contributing variables on life satisfaction in respondents. Approximately 83 % of subjects reported that they were satisfied with their current life. The results of multiple regression analysis showed that marital status (OR = 1.98), traditional treatments (OR = 0.43), social support (OR = 2.28) and educational level (OR = 1.79) significantly affected life satisfaction in samples (p < 0.05). Furthermore, age, ethnicity, sex differences, substance abuse and medical treatments were not significant predictors of life satisfaction (p > 0.05). It was concluded that social support, being married and education increased life satisfaction in subjects but traditional treatments decreased life satisfaction.