Advice from working women with retired partners

ABSTRACT

In the 21st century, as more women are employed full-time and couples increasingly share egalitarian values, more women continue employment after their partners have voluntarily retired. However, we know very little about the experiences of this growing population of women. We asked working women with retired partners to share their advice for other women who may face this developmental transition. Open-ended responses from 97 women were analyzed to identify pertinent issues and themes. Four primary content areas were identified: time management, division of household labor, financial planning, and communication. Communication between partners was both a topic of concern as well as the solution suggested to resolve conflicts or differences that may arise when women live with a retired partner. It is expected that future changes in the workforce and improvements in the gender balance within relationships will continue to impact experiences for working women with retired partners.     

Analyzing survival data in conjunction with time-dependent surrogate endpoints in clinical trials

Current survival techniques do not provide a good method for handling clinical trials with a large percent of censored observations. This research proposes using time-dependent surrogates of survival as outcome variables, in conjunction with observed survival time, to improve the precision in comparing the relative effects of two treatments on the distribution of survival time. This is in contrast to the standard method used today which uses the marginal density of survival time, T. only, or the marginal density of a surrogate, X, only, therefore, ignoring some available information. The surrogate measure, X, may be a fixed value or a time-dependent variable, X(t). X is a summary measure of some of the covariates measured throughout the trial that provide additional information on a subject's survival time. It is possible to model these time-dependent covariate values and relate the parameters in the model to the parameters in the distribution of T given X. The result is that three new models are available for the analysis of clinical trials. All three models use the joint density of survival time and a surrogate measure. Given one of three different assumed mechanisms of the potential treatment effect, each of the three methods improves the precision of the treatment estimate.