Sample size calculations for evaluating a diagnostic test when the gold standard is missing at random.

11:13 EDT 21st October 2014 | BioPortfolio

Summary of "Sample size calculations for evaluating a diagnostic test when the gold standard is missing at random."

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This article was published in the following journal.

Name: Statistics in medicine
ISSN: 1097-0258
Pages: 200

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Medical and Biotech [MESH] Definitions

The number of units (persons, animals, patients, specified circumstances, etc.) in a population to be studied. The sample size should be big enough to have a high likelihood of detecting a true difference between two groups. (From Wassertheil-Smoller, Biostatistics and Epidemiology, 1990, p95)

The process of gaining approval by a government regulatory agency for DIAGNOSTIC REAGENTS AND TEST KITS. This includes any required preclinical or clinical testing, review, submission, and evaluation of the applications and test results, and post-marketing surveillance.

Work consisting of a clinical trial involving one or more test treatments, at least one control treatment, specified outcome measures for evaluating the studied intervention, and a bias-free method for assigning patients to the test treatment. The treatment may be drugs, devices, or procedures studied for diagnostic, therapeutic, or prophylactic effectiveness. Control measures include placebos, active medicine, no-treatment, dosage forms and regimens, historical comparisons, etc. When randomization using mathematical techniques, such as the use of a random numbers table, is employed to assign patients to test or control treatments, the trial is characterized as a RANDOMIZED CONTROLLED TRIAL.

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Math calculations done for preparing appropriate doses of medicines, taking into account conversions of WEIGHTS AND MEASURES. Mistakes are one of the sources of MEDICATION ERRORS.

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