Uniformly best estimation in linear regression when prior information is fuzzy

Modeling prior information as a fuzzy set and using Zadeh’s extension principle, a general approach is presented how to rate linear affine estimators in linear regression. This general approach is applied to fuzzy prior information sets given by ellipsoidal α-cuts. Here, in an important and meaningful subclass, a uniformly best linear affine estimator can be determined explicitly. Surprisingly, such a uniformly best linear affine estimator is optimal with respect to a corresponding relative squared error approach. Two illustrative special cases are discussed, where a generalized least squares estimator on the one hand and a general ridge or Kuks–Olman estimator on the other hand turn out to be uniformly best.     

Hope: An affective cognition

Hope is here operationalized as a predominance of expected future positive feelings over future expected negative feelings. Hope, comprised of both desire and expectation, involves the interaction of affect and cognition. Modifications of Bradburn's Affective Balance Scale were used to measure hope and happiness. Four graphic rating scales were used to measure psychological well-being, perceived health, satisfaction, and happiness. Hope, measured by the Expected Balance Scale correlated as expected with the other measures. A factor analysis further supported the robustness of the hope variable. Hope is offered as an important personality dimension worthy of continued research.     

Home care: moving forward with continuous quality improvement

The utility of examining the effectiveness of home care is illustrated by selected examples and applications. The growth rate of home care over the past decade, questions regarding the possibly substantial differences between the quality of home care in rural and urban America, and empirical evidence that suggests inferior quality of home care for health maintenance organization patients support the need for measuring and monitoring outcomes of home care. The conclusions of a research program targeted at developing a system of outcome measures for home care, and the resulting national demonstration program to implement and refine that system, are summarized.     

TigerPlace, A State-Academic-Private Project to Revolutionize Traditional Long-Term Care

The Aging in Place Project at the University of Missouri (MU) required legislation in 1999 and 2001 to be fully realized. An innovative home health agency was initiated by the Sinclair School of Nursing specifically to help older adults age in place in the environment of their choice. In 2004, an innovative independent living environment was built and is operated by a private long term care company, as a special facility where residents can truly age in place and never fear being moved to a traditional nursing home unless they choose to do so. With care provided by the home care agency with registered nurse care coordination services, residents receive preventative and early illness recognition assistance that have markedly improved their lives. Evaluation of aging in place reveal registered nurse care coordination improves outcomes of cognition, depression, activities of daily living, incontinence, pain, and shortness of breath as well as delaying or preventing nursing home placement. Links with MU students, faculty, and nearly every school or college on campus enrich the lives of the students and residents of the housing environment. Research projects are encouraged and residents who choose to participate are enjoying helping with developing cutting technology to help other seniors age in place.