jamovi

Jamovi has a strange attitude toward adjusting for multiple comparisons. I sincerely understand the debatability and complexity of this issue. It would be helpful to allow the user to decide whether to adjust for multiple comparisons and provide a universal tool for various types of analysis. Less c...

I didn't find a ready-made R library

Some images

Dear Jamoviers! At the insistent request of @rabouqal, I completed the creation of the Uncertain Interval "Three-way threshold determination of medical tests" procedure in jYS module (R package from Hans Landsheer https://github.com/HansLandsheer/UncertainInterval ). While I was figuring i...

High Contrast colour pallettes in last version 2.7.8 is impressive.
Can we dream of a dark theme without activating high contrast mode in Windows?

Foe example I get the code as ggplot(data, aes(x, y, label = rownames(data))) and want to add another text, or legend p + geom_text() If this works, then it will be very useful. For example in my code something like this work fine: p <- ggmice::plot_pattern(data=dat, square=TRUE, rotate=TRUE) p <- ...

Venn Diagram:
- "show percentage labels" checkbox doesn't effect
- can you extend to more than four levels?

Beautiful plots and commentary texts!
But many of the results are in R output text format (preformatted).
I understand that this speeds up module development.

1. You must place test.js to jamovi/js folder 2. In the test.u.yaml - type: ActionButton name: myAction events: change: './test::myAction_clicked' 3. Alternatively, you can react to a button press in the test.b.R run function code: .run = function() { if (self$options$myAction) { ### code here } }

Hi, For regression analysis of explainers (Evaluation of MAR explainers), all variables (complete + incomplete) are used. The basis for imputation is created using the full array of variables you selected. Including incomplete variables in a separate group allows you to form output tables and pseudo...