Post hoc test for Trend analysis and other

Hi all,

I'm new to trend analysis and would like to get some advice.

My study is about treatment intervention on learning.
Between-subject variable is treatment group (treatment1, treatment2, no treatment) and within-subject variable is time (time1, time2, time3). My dependent variable is subject's task score on a behavioural test. I want to compare treatment effects on learning of the task.

First, I did two-way mixed ANOVA (aka split plot ANOVA). The main effect of time was significant but the interaction of treatment and time was not significant.

Next, trend analysis (or Within-subject contrast on SPSS) gave me good results;
Linear trend was significant and the interaction of linear trend was also significant.
If my understanding is correct, the significant interaction of the linear trend means that a linear trend of each group differs from at least one of the other groups..., right?

I would like to dig in this trend analysis because I'm interested in how learning curves/trends differ across the treatment groups.

Here are my questions;
1) Is there any post hoc test for trend analysis to see which treatment group differs from which treatment group?

2) How do you calculate the df of F value for the interaction of the linear trend? (I know this is a stupid question but I cannot find any good instruction.)

3) I'm not completely convinced by the fact that mixed ANOVA didn't show a significant interaction while linear trend interaction was significant. Can anyone provide me with any possible reason for this?

I use mainly R and SPSS and sometimes SAS, but I'm open to other softwares and manual analysis.

Any advice would be greatly appreciated.
Thank you in advance!