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Articles 61 - 65 of 65
Full-Text Articles in Clinical Epidemiology
Semi-Parametric Regression For The Area Under The Receiver Operating Characteristic Curve, Lori E. Dodd, Margaret S. Pepe
Semi-Parametric Regression For The Area Under The Receiver Operating Characteristic Curve, Lori E. Dodd, Margaret S. Pepe
UW Biostatistics Working Paper Series
Medical advances continue to provide new and potentially better means for detecting disease. Such is true in cancer, for example, where biomarkers are sought for early detection and where improvements in imaging methods may pick up the initial functional and molecular changes associated with cancer development. In other binary classification tasks, computational algorithms such as Neural Networks, Support Vector Machines and Evolutionary Algorithms have been applied to areas as diverse as credit scoring, object recognition, and peptide-binding prediction. Before a classifier becomes an accepted technology, it must undergo rigorous evaluation to determine its ability to discriminate between states. Characterization of …
Partial Auc Estimation And Regression, Lori E. Dodd, Margaret S. Pepe
Partial Auc Estimation And Regression, Lori E. Dodd, Margaret S. Pepe
UW Biostatistics Working Paper Series
Accurate disease diagnosis is critical for health care. New diagnostic and screening tests must be evaluated for their abilities to discriminate disease from non-diseased states. The partial area under the ROC curve (partial AUC) is a measure of diagnostic test accuracy. We present an interpretation of the partial AUC that gives rise to a new non-parametric estimator. This estimator is more robust than existing estimators, which make parametric assumptions. We show that the robustness is gained with only a moderate loss in efficiency. We describe a regression modelling framework for making inference about covariate effects on the partial AUC. Such …
The Analysis Of Placement Values For Evaluating Discriminatory Measures, Margaret S. Pepe, Tianxi Cai
The Analysis Of Placement Values For Evaluating Discriminatory Measures, Margaret S. Pepe, Tianxi Cai
UW Biostatistics Working Paper Series
The idea of using measurements such as biomarkers, clinical data, or molecular biology assays for classification and prediction is popular in modern medicine. The scientific evaluation of such measures includes assessing the accuracy with which they predict the outcome of interest. Receiver operating characteristic curves are commonly used for evaluating the accuracy of diagnostic tests. They can be applied more broadly, indeed to any problem involving classification to two states or populations (D = 0 or D = 1). We show that the ROC curve can be interpreted as a cumulative distribution function for the discriminatory measure Y in the …
The Association Of Fluid Intake With Total Natural-Cause Mortality, Coronary Heart Disease And Fatal Stroke, Jacqueline Chung Lun Chan
The Association Of Fluid Intake With Total Natural-Cause Mortality, Coronary Heart Disease And Fatal Stroke, Jacqueline Chung Lun Chan
Loma Linda University Electronic Theses, Dissertations & Projects
Hypohydration may be more widespread than realized since it does not always arouse a sense of thirst. When thirst is felt, it is often ignored, or satisfied before euhydration is achieved. There is growing evidence indicating that hypohydration contributes to acute and chronic illnesses, and to rheological factors associated with coronary heart disease (CHD) and stroke. Therefore the relationship of fluid intake with risk of total natural-cause mortality, CHD and stroke death was examined using data on 34,192 white, non-Hispanic participants in the Adventist Health Study.
Among the 27,342 reporting no CHD, stroke or diabetes at baseline, during six years …
Assessing The Accuracy Of A New Diagnostic Test When A Gold Standard Does Not Exist, Todd A. Alonzo, Margaret S. Pepe
Assessing The Accuracy Of A New Diagnostic Test When A Gold Standard Does Not Exist, Todd A. Alonzo, Margaret S. Pepe
UW Biostatistics Working Paper Series
Often the accuracy of a new diagnostic test must be assessed when a perfect gold standard does not exist. Use of an imperfect test biases the accuracy estimates of the new test. This paper reviews existing approaches to this problem including discrepant resolution and latent class analysis. Deficiencies with these approaches are identified. A new approach is proposed that combines the results of several imperfect reference tests to define a better reference standard. We call this the composite reference standard (CRS). Using the CRS, accuracy can be assessed using multistage sampling designs. Maximum likelihood estimates of accuracy and expressions for …