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Confusión en los estudios clínicos

Confusion in clinical studies

Abstract

The article refers to the implications of confusion in clinical trials. Classical examples of confusion variables are used to explain the concept and techniques are described that may prevent imbalances between groups in which variables may lead to confusion in results, such as matching and restriction.

Randomization is explained and is presented as a powerful tool that prevents confusion as it evenly distributes the variables between groups, both known variables and unknown variables.

The article describes that another approach to confusion is in phase of results analysis and options include stratified analysis and multivariate analysis.

The article concludes that in spite of all of these efforts, unknown residual confusion may still occur.