How experimental studies should be analyzed, presented, and interpreted in interval and semi-interval scales; Potential and pitfalls, with examples

Arash Akaberi, Yaser Tabarraie, Ehsan Ghasemi, Somayeh Zamiri, Mohammad Shafi Mojadadi

Abstract


Experimental studies have an undeniable role in the production of knowledge and are implemented to establish a cause and effect relationship between variables. But there are a range of biases that can affect the results of a study. In the meantime, even if the statistical method is being selected properly, the result may still be a bias due to confounding. Sometimes in data analysis we see that the statistical methods has not been properly selected and the substantial proportion of the incorrect use of statistical methods is related to experimental studies which are more sensitive than observational studies.

In this study we have provided one of the correct methods of analyzing experimental studies with examples and relevant commentary. We also have explored the pitfalls of experimental studies’ analysis.


Keywords


experimental studies, repeated measures analysis of variance, analysis of covariance, effectiveness.

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