Testing statistical hypotheses of equivalence by Stefan Wellek

By Stefan Wellek

Equivalence checking out has grown considerably in significance during the last 20 years, specifically as its relevance to numerous purposes has turn into understood. but released paintings at the basic technique continues to be scattered in experts' journals, and for the main half, it specializes in the quite slender subject of bioequivalence assessment.

With a much broader viewpoint, checking out Statistical Hypotheses of Equivalence offers the 1st accomplished therapy of statistical equivalence checking out. the writer addresses a spectrum of particular, two-sided equivalence checking out difficulties, from the one-sample challenge with more often than not allotted observations of mounted recognized variance to difficulties concerning a number of samples and multivariate facts. The therapy contains a concise overview of easy mathematical effects on optimum assessments for equivalence, and the writer makes on hand on the net a set of desktop courses that let effortless implementation of the tools presented.

In a box as advanced and wealthy in capability functions as equivalence trying out, trying out Statistical Hypotheses of Equivalence stands by myself as a coherent reference that furnishes either the theoretical and sensible instruments wanted for facing equivalence trials of any complexity and in any section.

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Extra info for Testing statistical hypotheses of equivalence

Example text

Sensitivity and specificity should be used to refer to the intrinsic diagnostic performance of a given examination while predictive values enable us to evaluate the reliability of the results of the same examination once it is permormed. It should be borne in mind that these are not the same thing, as we will explain by demonstrating the influence of disease prevalence on predictive values. 5). ) to perform the examination, and on the radiologist’s skill in interpreting the examination. Sensitivity and specificity are not influenced by the disease prevalence in the study population (they are instead influenced by the degree, the stage of the disease, as we will demonstrate in the next section).

For instance, if we state that computed tomography (CT) is highly “specific” for the diagnosis of intracranial hemorrhage, we would mean that this imaging modality can reliably identify a hyperattenuation on nonenhanced scans as a hemorrhage. However, this statement has two different meanings: if really there is an intracranial hemorrhage, it is highly probable that CT can detect it; a CT diagnosis of intracranial hemorrhage is rarely a false positive. Using correct scientific terminology, these two sentences are the same as saying that CT has both high sensitivity and high positive predictive value for intracranial hemorrhage.

Throughout the book the reader will find several mathematical formulas. These have been included in their entirety for the readers willing to understand the mechanism of computing. However, a thorough understanding of the formulas is by no means required to grasp the general sense of the concepts and their practical use. Introduction 15 It is far from our intention to educate radiologists so that they can replace statisticians, as this appears neither possible nor useful. Instead it is our aim educate radiologists so that they may interact with statisticians with proficiency and critical judgment.