Here is the linear mixed model that I am working with: 

```
p3 <- lmer(respTime ~ proc*farFC+(1 | Subject), dtINT)
```

Proc refers to a factor with 2 levels (adjacent and overlay)
farFC refers to a continous variable with 9 levels

The main output is below. 

[![enter image description here][1]][1]


The **slope of overlay is = 0.958**. 

When I change the reference level from adjacent to overlay, the **slope of adjacent is -0.958.** 

Here is the code for how I am changing the reference level: 

```
dtINT <- within(dtINT, proc <- relevel(proc, ref = 2)) 
#1 = ref level is overlay, 2 = ref level is adjacent
```

Why are the slopes the same but in opposite directions? Below is a graph, and we can see that the slopes are not the same (lines are not perfectly parallel). 

[![enter image description here][2]][2]

**How do I compute the slopes of each of these lines from the model? Said differently, how do I compute the slopes for each level of my IV? 
How do I tell if each of those slopes are significant?** 


  [1]: https://i.sstatic.net/zR6tb.png
  [2]: https://i.sstatic.net/LHacj.png