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Statistical methods.

The purpose of this chapter is to present a conceptual framework that applies to almost all statistical procedures discussed so far in this text. We also describe briefly, using a conceptual framework only, some of the more advanced techniques used in medicine.

Humans↗

Classification methods.

This chapter describes all the recent advances in statistical and syntactic pattern recognition, along with a number of the most important hybrid efforts in pattern recognition methodology, which together with structural pattern recognition, are the future trends in pattern recognition applications' schemes.

Bayes Theorem↗

Some problems with the investigation of noninferiority in meta-analysis.

OBJECTIVES: Noninferiority trials have become commonplace in recent years. Like individual clinical trials, meta-analyses can also investigate noninferiority. However, certain important topics have to be considered. METHODS: The proposed methods in this paper have their origin in the framework of noninferiority trials and meta-analyses. This paper can therefore be seen as a combination of both fields. Two issues are highlighted in the paper; difficulties in the choice of delta for a noninferiority meta-analysis leading to different deltas and methods for meta-analyses with different analysis sets, based on the full-analysis set with the intention-to-treat principle or the per-protocol population. Analytical methods, sensitivity analyses, meta-regression, and a bivariate method are introduced. The proposed graphical presentations support the analytical results. CONCLUSION: The confidence interval approach using meta-regression or bivariate methods is appropriate using both analysis sets for meta-analyses investigating noninferiority.

Clinical Trials as Topic↗

Weighted event rates.

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Evidence-Based Medicine↗