Timeline for Type of study without groups
Current License: CC BY-SA 3.0
10 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Mar 22, 2016 at 12:51 | vote | accept | Gilly | ||
| Mar 22, 2016 at 12:40 | answer | added | Giuseppe Biondi-Zoccai | timeline score: 2 | |
| Mar 22, 2016 at 12:01 | comment | added | Gilly | Let us continue this discussion in chat. | |
| Mar 22, 2016 at 11:47 | comment | added | Giuseppe Biondi-Zoccai | If sequence does not matter and analyses are completely independent then it's simply a comparison of paired data. Randomization is a feature relating to the underlying process. If such process is meaningless, then there is no randomized label to attach. | |
| Mar 22, 2016 at 11:39 | comment | added | Gilly | Maybe I can't find a name because it does not really count as a study? I'm not so sure anymore :S | |
| Mar 22, 2016 at 11:38 | comment | added | Gilly | I'm not sure. A before/after trial implies that the treatments are applied at different times with one (possibly) affecting the results of the other. I didn't mention specifically to keep the question as general as possible, but my project relates to applying different image processing methods to diagnostic images retrospectively. Each method can be applied completely independently. | |
| Mar 22, 2016 at 11:17 | comment | added | Giuseppe Biondi-Zoccai | Then it's simply a cross-over/before-after trial. But you could still randomize the sequence. For instance, half of the subjects will receive A and then B, and the other half B and then A. | |
| Mar 22, 2016 at 11:15 | comment | added | Gilly |
No, no randomisation at all. I want to test the effect of A vs. B, so I apply A to all subjects, and apply B to all as well, then compare the results. This should be valid for deterministic systems, like algorithms. So I suppose its not a trial at all. But it still is a study - what do you call it?
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| Mar 22, 2016 at 11:07 | comment | added | Giuseppe Biondi-Zoccai | I am not sure what you are talking about. Do you have multiple units of randomization per subject (eg two eyes in a man or four wheels in a car)? Then it's going to be a randomization with clustering. Quasi applies to non-random allocation, as far as I am aware (eg date of birth, which may be correlated with some features). | |
| Feb 18, 2016 at 5:18 | history | asked | Gilly | CC BY-SA 3.0 |