jamovi

Hi Oliver, The correlation matrix plots use the GGally R package in the background. To create the scatter plot with regression line the ggally_smooth function (see https://ggobi.github.io/ggally/reference/ggally_smooth.html ) is used. Here you can see that the interval around the regression line rep...

Hi everybody, So first let me reply to the following: That's one way to look at it. But the way I see it, the only correct way to reverse-code is to base it on the theoretical, not the actual range of the data. For example, for -2 to 2 scale [Strongly Disagree, Disagree, Neutral, Agree, Strongly Agr...

Thank you for bringing this bug to our attention! I found where the problem was and fixed it in this Pull Request: https://github.com/jamovi/jmv/pull/427.

It's strange that it previously didn't happen with the same file, as the library that we're using to make these plots (ggrides) hasn't changed in over a year. I looked into the issue and it indeed has to do with groups having 2 or fewer data points. However, I looked into the issue and it seems that...

Hi! I found the issue: it’s due to how each analysis handles missing values. The correlation matrix uses pairwise deletion, while the reliability analysis applies listwise deletion. Since your dataset has a lot of missing data, listwise deletion removes far more cases than pairwise deletion. When I ...

So the problem was that we were passing on data objects in an inefficient way. I made an improvement to the library that should fix your issue (See https://github.com/jamovi/jmv/pull/412). Jonathon will push out an update for jamovi in the next couple of days.

Thank you for reporting this issue!

Hi Jorge,

I'll have a look today to see what the problem is.

Cheers,
Ravi

I think that probably the path between 7 and 8 is missing because the items overlap and therefore occlude the path that is drawn between them. I expect that if it were possible to increase the height of the plot (which is not possible in jamovi at the moment), the path between 7 and 8 would show up ...

Hi Deniz, Maurizio is indeed right that in your first example ("Car_Level 1", "Car2_Level 1", "Car3_Level 1", and "Car4_Level 1") only 1 row/case remains after deleting all the missing values (jamovi uses listwise deletion in the reliability analysis), and as ...

So in terms of what's going wrong in the model is that it seems that the data you are using in the model are highly collinear resulting in a singular fit. You can see in the data that the `CP not having` level of `rec_owningageCP` and the `Non-use` level of `Rec_use_years` only occur together (and n...