Before talking about the differences of the comparisons, you need to know one important thing. Some of the post-hoc comparisons may not be appropriate for repeated-measure ANOVA. I am not 100% sure about this point, but it seems that some of the methods do not consider the within-subject design.
http://yatani.jp/teaching/doku.php?id=hcistats:posthoc
Not to be confused with Post hoc theorizing. In the design and analysis of experiments, post hoc analysis (from Latin post hoc, after this) consists of looking at the data—after the experiment has concluded—for patterns that were not specified a priori.
https://en.wikipedia.org/wiki/Post-hoc_analysis
Post hoc ergo propter hoc (Latin : after this, therefore because of this) is a logical fallacy (of the questionable cause variety) that states Since event Y followed event X, event Y must have been caused by event X.. It is often shortened to simply post hoc fallacy.
https://en.wikipedia.org/wiki/Post_hoc_ergo_propter_hoc
Post hoc tests — also known as a posteriori tests — greatly expand the range and capability of methods that can be applied in exploratory research.
https://en.wikipedia.org/wiki/Post-hoc_analysis
In the wider and more useful sense, post hoc analysis tests enable protection from the multiple comparisons problem, whether the inferences made are selective or simultaneous. The type of inference is related directly to the hypotheses family of interest.
https://en.wikipedia.org/wiki/Post-hoc_analysis
In practice, post hoc analyses are usually concerned with finding patterns and/or relationships between subgroups of sampled populations that would otherwise remain undetected and undiscovered were a scientific community to rely strictly upon a priori statistical methods.
https://en.wikipedia.org/wiki/Post-hoc_analysis
[Case 4] Compare the data against the within-subject factor: In this case, you will make a comparison against the within-subject factor. In other words, if you have done repeated-measure ANOVA, this is the way to do a post-hoc test. The methods for this case can be used for tests against between-subject factors.
http://yatani.jp/teaching/doku.php?id=hcistats:posthoc
The strict definition of a post-hoc test means a test which does not require any plan for testing. In the four examples above, only Case 1 satisfies the strict definition of a post-hoc test because the others cases require some sort of planning on which groups to compare or not to compare.
http://yatani.jp/teaching/doku.php?id=hcistats:posthoc
If you use the Anova() function, the way to do a Tukey's test is a little different. Here, we use the same example of two-way ANOVA, but the values for Time were slightly changed (to make the interaction effect disappear). With the anova test, you will find the main effects.
http://yatani.jp/teaching/doku.php?id=hcistats:posthoc
Post hoc is a particularly tempting error because temporal sequence appears to be integral to causality. The fallacy lies in coming to a conclusion based solely on the order of events, rather than taking into account other factors that might rule out the connection.
https://en.wikipedia.org/wiki/Post_hoc_ergo_propter_hoc
define post hoc
Post hoc is a particularly tempting error because temporal sequence appears to be integral to causality. Post hoc is a particularly tempting error because the temporal sequence appears to be integral to causality.