Journal ArticleDOI
Comparison of quantitative diagnostic tests: Type I error, power, and sample size
TLDR
The power and required sample size are studied for Gaussian and log-Gaussian distributions of diagnostic test values and the results may be useful for the planning phase of studies to evaluate quantitative diagnostic tests.Abstract:
For a quantitative laboratory test the 0.975 fractile of the distribution of reference values is commonly used as a discrimination limit, and the sensitivity of the test is the proportion of diseased subjects with values exceeding this limit. A comparison of the estimates of sensitivity between two tests without taking into account the sampling variation of the discrimination limits can increase the type I error to about seven times the nominal value of 0.05. Correct statistical procedures are considered, and the power and required sample size are studied for Gaussian and log-Gaussian distributions of diagnostic test values. The results may be useful for the planning phase of studies to evaluate quantitative diagnostic tests.read more
Citations
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Receiver-Operating Characteristic Analysis for Evaluating Diagnostic Tests and Predictive Models
TL;DR: The measures of accuracy—sensitivity, specificity, and area under the curve (AUC)—that use the ROC curve are reviewed, and how these measures can be applied using the evaluation of a hypothetical new diagnostic test as an example are illustrated.
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Sample size estimation in diagnostic test studies of biomedical informatics
TL;DR: This review provided a conceptual framework of sample size calculations in the studies of diagnostic test accuracy in various conditions and test outcomes to help clinicians when designing diagnostic test studies that an adequate sample size is chosen based on statistical principles in order to guarantee the reliability of study.
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A family of nonparametric statistics for comparing diagnostic markers with paired or unpaired data
TL;DR: In this paper, a broad class of nonparametric statistics for comparing two diagnostic markers is studied, and test procedures and confidence intervals are based on asymptotic normality.
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ROC analysis
TL;DR: This review summarizes the fundamental concepts of ROC analysis and the interpretation of results using examples of sequence and structure comparison and overview the available programs and evaluation guidelines for genomic/proteomic data.
References
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TL;DR: In this paper, the basic theory of Maximum Likelihood Estimation (MLE) is used to detect a difference between two different proportions of a given proportion in a single proportion.
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An Analysis of Transformations
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Statistical Methods for Rates and Proportions
R. L. Plackett,Joseph L. Fleiss +1 more
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TL;DR: Lloyds Bank has its main root in a substantial private bank founded in Birmingham nearly two centuries ago; one hundred years ago this Bank still had only the one office in Birmingham, with a related private banking house in Lombard Street, and by amalgamation it has absorbed scores of other eighteenth and nineteenth century banks, both private and joint stock, and at least two of the former reach back into Restoration London, perhaps Cromwellian London.
Book
The lognormal distribution
TL;DR: Lloyds Bank has its main root in a substantial private bank founded in Birmingham nearly two centuries ago; one hundred years ago this Bank still had only the one office in Birmingham, with a related private banking house in Lombard Street, and by amalgamation it has absorbed scores of other eighteenth and nineteenth century banks, both private and joint stock, and at least two of the former reach back into Restoration London, perhaps Cromwellian London.