Intention-to-Treat Principle vs Treatment Received Analysis

What is the intention-to-treat (ITT) principle in clinical trials?

Why do most statisticians favor the ITT principle in clinical trials?

What is considered a critical component of the ITT Principle to avoid biases in clinical trials?

According to the E9 document, under what circumstances can randomized patients be excluded from the full analysis set?

Why do federal agencies favor the ITT principle in clinical trials?

What does 'If randomized, then analyzed' represent in clinical trial methodology?

Under what circumstances can patients who failed to satisfy an entry criterion be excluded from the full analysis set?

Why could the placebo group appear more beneficial than the new therapy in an ITT analysis according to the given example?

What can eliminate the problem of misleading results from the ITT analysis, as mentioned in the text?

What is identified as a factor contributing to a patient's failure to complete the intended therapy in the text?

What is preferred as the primary endpoint in situations where ITT analysis could be misleading?

Why does the text state that patients cannot be eliminated from analysis for certain reasons?

What is the intention-to-treat (ITT) principle in clinical trials?

Why do federal agencies favor the ITT principle in clinical trials?

What can eliminate the problem of misleading results from the ITT analysis, as mentioned in the text?

What is identified as a factor contributing to a patient's failure to complete the intended therapy in the text?

Under what circumstances can patients who failed to satisfy an entry criterion be excluded from the full analysis set?

What does 'If randomized, then analyzed' represent in clinical trial methodology?

What type of study design is considered the 'gold standard' for establishing a causal relationship between intervention and outcome?

What is the name of the analysis that evaluates patients according to the group they were originally assigned to?

What can introduce bias into the study and analysis even in the correct implementation of a valid random allocation sequence?

What can disrupt the prognostic balance afforded by randomization and introduce bias into the study and analysis?

What is the most effective way to establish a causal relationship between an intervention and outcome, according to the text?

When randomization is done correctly, what are the groups balanced with regard to, except for the intervention?

What does an investigator observe in two (or more) groups that are prognostically balanced, with the exception of the intervention?

What is the name of the principle that can lead to a significantly biased assessment of the effectiveness of an intervention if not applied when interpreting results from a randomized trial?

What does preserving the integrity of randomization during the implementation of the study and in analysis help guard against, as mentioned in the text?