George J. Knafl

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Regression methods are used to model fault detection effectiveness in terms of several product and testing process measures. The relative importance of these product/process measures for predicting fault detection effectiveness is assessed for a specific data set. A substantial family of models is considered, specifically, the family of quadratic response(More)
Outcome measurements from members of the same family are likely correlated. Such intrafamilial correlation (IFC) is an important dimension of the family as a unit but is not always accounted for in analyses of family data. This article demonstrates the use of linear mixed modeling to account for IFC in the important special case of univariate measurements(More)
BACKGROUND Hospitalization contributes enormously to health care costs associated with heart failure. Many investigators have attempted to predict hospitalization in these patients. None of these models has been highly effective in prediction, suggesting that important risk factors remain unidentified. PURPOSE To assess prospectively collected medication(More)
BACKGROUND Electronic monitoring devices (EMDs) are regarded as the "gold standard" for assessing medication adherence in research. Although EMD data provide rich longitudinal information, they are typically not used to their maximum potential. Instead, EMD data are usually combined into summary measures, which lack sufficient detail for describing complex(More)
BACKGROUND Medication nonadherence is a major cause of hospitalization in patients with heart failure (HF), which contributes enormously to health care costs. We previously found, using the World Health Organization adherence dimensions, that condition and patient level factors predicted nonadherence in HF. In this study, we assessed a wider variety of(More)