jamovi

We have a bipolar scale that asks do you agree with A more or b more

It happened to be coded this way
(1) completely agree with A <--> (7) completely agree with B
So (4) is indifference

It should have been coded this way:
(-3) completely agree with A <--> (3) completely agree with B
So (0 is indifference)

In a regression our agreement scale is a control to see whether the difference between two conditions can be explained by agreement. E.g. person A seems to be liked significantly more, is this just because most people agree person A more than person B. (Agree is the control Like is DV).
You can see the graphs are the same but the numbers at the x axis are different because of the different coding. But for the graph on the left there is a significant main effect of condition (p < .001) and on the right the main effect disappears (p = 0.546) (i.e. is explained by agreement)

I know the right one is correct but I didn't realise the coding would make a difference in regression. Can anyone explain why I need to make sure indifference is at 0 on bipolar scales? The only thing I can think of is that -3 and 3 have the same absolute value
but 1 and 7 don't but I am not sure why absolute value needs to be calculated.

It seems the issue is related to centering, not the scale scoring. But, if you show me your regression model, I can figure out the reason.

Thanks Simonmoon!

Actually this problem was solved (see here: https://forum.cogsci.nl/discussion/8413 ... ion#latest)