But what's the difference between per protocol & completers-only analysis? Sounds like same, as in both cases who adhered to initial randomly allocated group & present till end of the study are been considered.! 4:12imputation methods
I am still confused how if we don't know the outcome of the dropped out subjects? For example, 100 subjects in control group vs 100 subjects in experimental group are followed for survival after 5 years. If there are 10 dropped out subjects in experimental group and (for the sake of simplicity) the rest of them is alive, how should we calculate the survival rate of experimental group? PP analysis: 90/90 = 100% ITT analysis: 90/100? And how about if I study their mortality rate? PP analysis: 0/90 = 0% ITT analysis: 10/100 = 10% (we count the dropped out subjects as "failure") or 0/100 (because we only include the dropped out as they were randomized, without any outcome)? Thank you
"statistical analysis Statistical analysis should have analysis principles such as ITT or PP. In addition, imputation methods for dropout should be suggested." there is a revision. I watched this video to handle this revision but I could not understand how I can solve it. Could you please help me? what is the expectation of reviewers or editors related to this revision? what should I add to the manuscript? Thank you very much..
“The advantages of randomization…” are presumably for the experimenter who wants to follow his intentions. Unfortunately all kinds of disappointing outcomes have good intentions. But, if the patient died before they took the pill they are not in the experiment. In fact, intention to treat requires that you report that death is an outcome of the trial which may be a test of dental carries prevention. Proponents of using intention to treat will never answer objections like that. They might have to say that that was not the outcome. To determine the outcome, they will examine the teeth of the corpse.
But what's the difference between per protocol & completers-only analysis? Sounds like same, as in both cases who adhered to initial randomly allocated group & present till end of the study are been considered.!
4:12imputation methods
This was excellent, exactly what I was looking for. Thank you!
I am still confused how if we don't know the outcome of the dropped out subjects? For example, 100 subjects in control group vs 100 subjects in experimental group are followed for survival after 5 years. If there are 10 dropped out subjects in experimental group and (for the sake of simplicity) the rest of them is alive, how should we calculate the survival rate of experimental group?
PP analysis: 90/90 = 100%
ITT analysis: 90/100?
And how about if I study their mortality rate?
PP analysis: 0/90 = 0%
ITT analysis: 10/100 = 10% (we count the dropped out subjects as "failure") or 0/100 (because we only include the dropped out as they were randomized, without any outcome)?
Thank you
your videos are very good and have a wide message thank you
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Excellent explanation
A very easy to learn way
"statistical analysis
Statistical analysis should have analysis principles such as ITT or PP. In addition, imputation methods for dropout should be suggested." there is a revision. I watched this video to handle this revision but I could not understand how I can solve it. Could you please help me? what is the expectation of reviewers or editors related to this revision? what should I add to the manuscript? Thank you very much..
“The advantages of randomization…” are presumably for the experimenter who wants to follow his intentions. Unfortunately all kinds of disappointing outcomes have good intentions. But, if the patient died before they took the pill they are not in the experiment. In fact, intention to treat requires that you report that death is an outcome of the trial which may be a test of dental carries prevention. Proponents of using intention to treat will never answer objections like that. They might have to say that that was not the outcome. To determine the outcome, they will examine the teeth of the corpse.
Thanks very much. Bery useful
Thank you so much
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