# Interpret repeated measures ANOVA results in R

I developed many model on groups of data I applied repeated measures anova to check the significant difference. Then I applied pairwise.t.test using Bonferroni correction.

I got this result from the anova test:

    Error: data
Df    Sum Sq   Mean Sq F value Pr(>F)
Residuals  9 6.533e-05 7.259e-06

Error: data:model
Df    Sum Sq   Mean Sq F value Pr(>F)
model      15 0.0007337 4.892e-05    25.4 <2e-16 ***
Residuals 135 0.0002600 1.930e-06
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1


What am not sure about it is how to interpret this result, I understand that there is a significant difference because there is ***, but:

1. what does the F-value mean? what should I compare it to?
2. should I compare the pr to p-value(0.05)? the pr is 2e-16 which is too small number so what this means?
3. after applying the pairwise.t.test, this is the result:

     m1      m10     m11     m12     m13     m14     m15     m16     m2      m3      m4
m10 1.00000 -       -       -       -       -       -       -       -       -       -
m11 1.00000 1.00000 -       -       -       -       -       -       -       -       -
m12 1.00000 1.00000 1.00000 -       -       -       -       -       -       -       -
m13 0.00011 2.7e-07 6.1e-06 0.01300 -       -       -       -       -       -       -
m14 0.00167 5.9e-06 0.00011 0.12148 1.00000 -       -       -       -       -       -
m15 1.3e-10 1.0e-13 3.9e-12 6.4e-08 0.98736 0.14375 -       -       -       -       -
m16 4.0e-08 4.2e-11 1.4e-09 1.2e-05 1.00000 1.00000 1.00000 -       -       -       -
m2  1.00000 0.34365 1.00000 1.00000 0.12397 0.86949 1.6e-06 0.00022 -       -       -
m3  1.00000 1.00000 1.00000 1.00000 1.3e-05 0.00022 9.3e-12 3.2e-09 1.00000 -       -
m4  1.00000 1.00000 1.00000 1.00000 0.02063 0.18257 1.2e-07 2.2e-05 1.00000 1.00000 -
m5  0.14672 1.00000 1.00000 0.00211 4.1e-12 1.4e-10 < 2e-16 3.0e-16 0.00014 0.64775 0.00127
m6  1.00000 1.00000 1.00000 1.00000 0.01057 0.10112 4.8e-08 9.4e-06 1.00000 1.00000 1.00000
m7  0.59267 1.00000 1.00000 0.01218 5.0e-11 1.6e-09 < 2e-16 4.1e-15 0.00097 1.00000 0.00759
m8  1.00000 1.00000 1.00000 1.00000 1.3e-06 2.6e-05 6.1e-13 2.4e-10 0.87263 1.00000 1.00000
m9  1.00000 1.00000 1.00000 1.00000 1.8e-07 4.2e-06 6.5e-14 2.8e-11 0.27244 1.00000 1.00000


Does this mean that only p-values under (0.05) in this table indicate there are significant difference? so there is no significant difference between m1 and m10 because the p-value is 1, but there is a significant difference between m12 and m13 because the p-value is 0.01300?