multiple paired t-test In the multiple testing problem for independent samples, general procedure is one way ANOVA followed by Tukey's HSD or Scheffe’s Method. 
For multiple dependent samples, one way ANOVA is replaced by repeated measure ANOVA. But what is the analogy of Tukey or Scheffe in the dependent sample setting?
 A: In statistical design the generalization of pair is block, so I think you are looking for a block design.
For example, if three types of chocolate are being rated
for flavor by a panel of 15 professional tasters, then you would have a
two-way ANOVA with factors Type and Taster, and one Flavor score for each Type by each Taster. (Altogether: 45 observations.) One hopes that
professional Tasters have more or less fixed standards
so that the variation among them is not a major issue
of the data analysis.
The main goal is to see if
there are statistically significant differences among Types. The main F-test for Type establishes that factor as significant. The bottom line for you is that there is a way
to apply Tukey's HSD method to Types for post hoc analysis of this two-way
ANOVA. [Because there is only one rating score per cell, this model does not have an interaction term.]
This R-Bloggers page shows which R procedures to use
and the syntax for using them. [The example, originally
written in Portuguese and translated to English, retains
Portuguese variable names: Sabor for flavor score, Tipo for type of chocolate, and Provador for taster.]
