Elderly African Americans as intragenerational caregivers

A growing number of older Americans serve as caregiving resources for their elderly spouses, partners, relatives, and/or friends. Yet, little research has addressed the impact and implications of this trend among African Americans. This article describes the results of a qualitative study examining the intragenerational caregiving experiences and perspectives of two cohorts of African Americans (urban and rural, N = 129) between the ages of 58 and 89. Its findings reveal important differences and commonalities associated with elderly African American caregivers and their care giving in urban and rural settings. Additionally, the study suggests that volunteer caregivers can often fill the void left by partners and relatives who predecease or fail to assume responsibility for the care of their elderly relatives. Their efforts do not displace those of friends and family members, but rather address unmet needs in available care. The discussion focuses on the implications of the study findings for public policy and practice.     

Maximum Value of Hotelling's T 2 Statistics Based on the Successive Differences Covariance Matrix Estimator

In statistical process control applications, the multivariate T ² control chart based on Hotelling's T ² statistic is useful for detecting the presence of special causes of variation. In particular, use of the T ² statistic based on the successive differences covariance matrix estimator has been shown to be very effective in detecting the presence of a sustained step or ramp shift in the mean vector. However, the exact distribution of this statistic is unknown. In this article, we derive the maximum value of the T ² statistic based on the successive differences covariance matrix estimator. This distributional property is crucial for calculating an approximate upper control limit of a T ² control chart based on successive differences, as described in Williams et al. (2006 Williams , J. D. , Woodall , W. H. , Birch , J. B. , Sullivan , J. H. ( 2006 ). On the distribution of T ² statistics based on successive differences . J. Qual. Technol. 38 : 217 – 229 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]).     

Tests for the two-sample problem based on empirical probability measures

Tests are proposed for the equality of two unknown distributions. For empirical probability measures that are defined for samples from the two distributions, the proposed tests are based on the supremum of the absolute differences between the corresponding empirical probabilities, the supremum being taken over all possible events (Borel sets). In contrast, competing EDF tests compare only empirical probabilities of a subclass of Borel sets. The proposed tests are compared for simulated samples to the Kolmogorov-Smirnov, Cramér-von Mises, Kuiper, and Mann-Whitney-Wilcoxon tests     

A counterexample to a claim concerning the convolution of multimodal distributions

P. Ghosh (1981) has claimed that the convolution of two symmetric multimodal distributions is symmetric and unimodal. A simple counterexample to this claim is constructed by considering the convolution f?f, where f is an appropriate mixture of two normal densities.

     

Simulation-Based Tests that Can Use Any Number of Simulations

Conventional procedures for Monte Carlo and bootstrap tests require that B, the number of simulations, satisfy a specific relationship with the level of the test. Otherwise, a test that would instead be exact will either overreject or underreject for finite B. We present expressions for the rejection frequencies associated with existing procedures and propose a new procedure that yields exact Monte Carlo tests for any positive value of B. This procedure, which can also be used for bootstrap tests, is likely to be most useful when simulation is expensive.     

Alternative Factors for Control Chart Construction

Conflicting decision signals resulting from Shewhart Mean and Variability Control Charts produce undesirable consequences. Therefore, we construct “six-sigma” control charts by alternative methods to avoid problems associated with Control Charts yielding different signals. By adjusting methods for control chart construction for dispersion charts, we produce new reference tables. The new tables provide consistent signals and appear similar and familiar to users of historical tables.     

The Need to Reconcile Concepts that Characterize Systems Facing Threats

Desirable system performance in the face of threats has been characterized by various management concepts. Through semistructured interviews with editors of journals in the fields of emergency response and systems management, a literature review, and professional judgment, we identified nine related and often interchangeably used system performance concepts: adaptability, agility, reliability, resilience, resistance, robustness, safety, security, and sustainability. A better understanding of these concepts will allow system planners to pursue management strategies best suited to their unique system dynamics and specific objectives of good performance. We analyze expert responses and review the linguistic definitions and mathematical framing of these concepts to understand their applications. We find a lack of consensus on their usage between interview subjects, but by using the mathematical framing to enrich the linguistic definitions, we formulate comparative visualizations and propose distinct definitions for the nine concepts. We present a conceptual framing to relate the concepts for management purposes.     

Modeling time series data with semi-reflective boundaries

Time series data are increasingly common in many areas of the health sciences, and in some instances, may have natural boundaries serving as performance guidelines or as thresholds associated with adverse outcomes. Such boundaries may be labeled as semi-reflective, in that the time series values have an increased chance of returning towards middle levels as the boundaries are approached, but boundaries can still be breached. In this paper we review a model that was previously proposed for such data and we investigate its statistical properties. Specifically, this model consists of a third-order auto-regressive projection component, parameterized as a constrained linear combination of linear, flat, and quadratic trends, and an error term that uses a logistic regression model for its sign. We describe and compare a previously-proposed estimation method with a modified version thereof, using computer simulations, as well as data examples from heart monitoring and from a driving simulator. We find that the two methods tend to give different results, with the modified technique having lower bias and more accurate confidence intervals than the previously-proposed method.     

You Shall (Not) Pass: Strategies for Third-Party Gatekeepers to Enhance Volunteer Inclusion

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - Volunteering appears to be a mechanism that can contribute to societal inclusion. As nonprofit organizations continuously...     

The Practical Significance of Measurement Error in Pulmonary Function Testing Conducted in Research Settings

Conventional spirometry produces measurement error by using repeatability criteria (RC) to discard acceptable data and terminating tests early when RC are met. These practices also implicitly assume that there is no variation across maneuvers within each test. This has implications for air pollution regulations that rely on pulmonary function tests to determine adverse effects or set standards. We perform a Monte Carlo simulation of 20,902 tests of forced expiratory volume in 1 second (FEV₁), each with eight maneuvers, for an individual with empirically obtained, plausibly normal pulmonary function. Default coefficients of variation for inter‐ and intratest variability (3% and 6%, respectively) are employed. Measurement error is defined as the difference between results from the conventional protocol and an unconstrained, eight‐maneuver alternative. In the default model, average measurement error is shown to be ～5%. The minimum difference necessary for statistical significance at p < 0.05 for a before/after comparison is shown to be 16%. Meanwhile, the U.S. Environmental Protection Agency has deemed single‐digit percentage decrements in FEV₁ sufficient to justify more stringent national ambient air quality standards. Sensitivity analysis reveals that results are insensitive to intertest variability but highly sensitive to intratest variability. Halving the latter to 3% reduces measurement error by 55%. Increasing it to 9% or 12% increases measurement error by 65% or 125%, respectively. Within‐day FEV₁ differences ≤5% among normal subjects are believed to be clinically insignificant. Therefore, many differences reported as statistically significant are likely to be artifactual. Reliable data are needed to estimate intratest variability for the general population, subpopulations of interest, and research samples. Sensitive subpopulations (e.g., chronic obstructive pulmonary disease or COPD patients, asthmatics, children) are likely to have higher intratest variability, making it more difficult to derive valid statistical inferences about differences observed after treatment or exposure.