Carol S. Aneshensel presents a method for bringing data analysis and statistical technique into line with theory. She approaches this task by providing an overview that explains the connection between data analysis, statistical technique and theory.
Given medical advances and greater understanding of healthful living habits, people are living longer lives. Proportionally speaking, a greater percentage of the population is elderly. Despite medical advances, there is still no cure for dementia, and as elderly individuals succumb to Alzheimer's Disease or related dementia, more and more people are having to care their elderly parents and /or siblings. Profiles in Caregiving is practical source of information for anyone who teaches caregiving, acts as a caregiver, or studies caregiving. This book discusses recent research on stress factors associated with caregiving, and what factors impact on successful versus non-successful adaptation to the care-giving role. This is an expanding field in gerontology, and is also of interest to personality and social psychologists studying stress and interpersonal relations. Although there are many books on the cause and treatment of dementia, there has been a book that provides a research investigation into the factors associated with effective caregiving to dementia patients. Conceptualizes caregiving as a multistage career whose impact on the caregiver continues to be felt after in-home care has ceased Based upon a longitudinal survey of a demographically diverse sample of principal caregivers over a three-year period Identifies caregivers who are most at-risk for adverse adaptation to the role Describes preventative and clinical intervention strategies Identifies post-care risk and issues Identifies antecedents to successful adaptation State of the art analytic techniques Graphic presentation of empirical findings Renowned multidisciplinary research team
This book presents the elaboration model for the multivariate analysis of observational quantitative data. This model entails the systematic introduction of "third variables" to the analysis of a focal relationship between one independent and one dependent variable to ascertain whether an inference of causality is justified. Two complementary strategies are used: an exclusionary strategy that rules out alternative explanations such as spuriousness and redundancy with competing theories, and an inclusive strategy that connects the focal relationship to a network of other relationships, including the hypothesized causal mechanisms linking the focal independent variable to the focal dependent variable. The primary emphasis is on the translation of theory into a logical analytic strategy and the interpretation of results. The elaboration model is applied with case studies drawn from newly published research that serve as prototypes for aligning theory and the data analytic plan used to test it; these studies are drawn from a wide range of substantive topics in the social sciences, such as emotion management in the workplace, subjective age identification during the transition to adulthood, and the relationship between religious and paranormal beliefs. The second application of the elaboration model is in the form of original data analysis presented in two Analysis Journals that are integrated throughout the text and implement the full elaboration model. Using real data, not contrived examples, the text provides a step-by-step guide through the process of integrating theory with data analysis in order to arrive at meaningful answers to research questions.
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.