End-of-Life Conversations and Hospice Placement: Association with Less Aggressive Care Desired in the Nursing Home

Education about end-of-life care and treatment options, communication between family and health care providers, and having advance directives and medical orders in place are important for older adults with chronic, progressive decline and end-stage disease who spend their last days in the nursing home. This study used retrospective data (6 months before death) of long-stay nursing home decedents (N?=?300) taken from electronic health records to capture the end-of-life experience. Findings showed for almost all decedents, Do Not Resuscitate and Do Not Intubate orders were in place, and just over one-half had Do Not Hospitalize and No Artificial Feeding orders in place. A small proportion had No Artificial Hydration or No Antibiotic orders in place. Overall, there was congruence between documented medical orders and treatment received. Findings showed that use of hospice and discussions about particular life-sustaining treatments each had significant associations with having less aggressive medical orders in place. These results can inform best practice development to promote high quality, person-directed, end-of-life care for nursing home residents.     

An omnibus test of goodness-of-fit for conditional distributions with applications to regression models

We introduce an omnibus goodness-of-fit test for statistical models for the conditional distribution of a random variable. In particular, this test is useful for assessing whether a regression model fits a data set on all its assumptions. The test is based on a generalization of the Cramér–von Mises statistic and involves a local polynomial estimator of the conditional distribution function. First, the uniform almost sure consistency of this estimator is established. Then, the asymptotic distribution of the test statistic is derived under the null hypothesis and under contiguous alternatives. The extension to the case where unknown parameters appear in the model is developed. A simulation study shows that the test has good power against some common departures encountered in regression models. Moreover, its power is comparable to that of other nonparametric tests designed to examine only specific departures.     

Enabling disruptive innovations through the use of customer analysis methods

The theory of disruptive innovation has had a profound effect on academic literature and management mindsets. Nevertheless, the processes that are required to develop disruptive innovations are not yet well understood. An essential part of creating disruptive innovations is gathering the right information on potential and current customers. The research questions that are addressed in this paper deal with the suitability of customer analysis methods for providing this information. The customer analysis model that is formulated in this paper summarizes the results of a literature review regarding the requirements of customer analysis for the success of disruptive innovations. With insights on context, customers, constraints and effects, the model reveals what information is needed to successfully shape the disruptive innovation process. Following the literature on disruptive and radical innovation, a group of eight customer analysis methods is selected and assessed. The analysis reveals that none of the existing methods can generate all of the required information. By combining and modifying the associated methods, the requirements of the proposed model and, by extension, the market can be met. Managers who follow the suggestions of this paper will develop a better understanding of current and potential customers and, therefore, unveil the potential of disruptive innovations.     

Quasi Most Powerful Invariant Goodness-of-fit Tests

ABSTRACT.  In this paper, we develop an approximation for the most powerful invariant test of one location-scale family against another one. The approach is based on the Laplace method for integrals and yields a very accurate approximation of the density of a maximal invariant. Moreover, it can be applied to a much wider set of pairs of densities than previously possible. Many examples are worked out. The resulting test is easy to compute and its power is shown to be very close to that of the best test. By using versions of the Laplace method, the approach is extended to goodness-of-fit tests for residuals in regression and to some multivariate distributions. A small simulation study confirms the theoretical results. An example concludes the paper.     

Uniqueness of the least-distances estimator in regression models with multivariate response

In a regression model with univariate response, the quantities derived from the least-absolute-deviations method need not be unique. In this note, we show that, contrary to the univariate case, in a regression model with multivariate response, the least-distances method typically yields quantities that exhibit uniqueness properties that are similar to those obtained by the least-squares method.     

The Conundrum of Low Saving Rates in Latin America

Despite extensive economic reforms during the late 1980s/early 1990s, Latin America's saving rates remain low. This article examines the saving behaviour of 18 Latin American countries in the 1976‐2000 period and compares it with that of 25 other developing countries. It finds that lower inflation, income growth and increased real interest rates on deposits have not had the expected effects on saving rates in Latin America. Instead, the determinants of saving behaviour appear to differ between the two groups of countries, and saving rates are affected by a degree of inertia. Although more research is needed, this indicates that the focus of the neoliberal economic reforms of the 1980s was misplaced.