jamovi

@Ravi The esci module appears to be calculating an effect size (and CI) for the difference between two means computed from paired samples, somehow taking the pairing into account, but NOT simply calculating the effect size (and CI) for difference scores.

@Andrzej_Andrew It is also common, after a chi square analysis, to want to know about proportions or ratios pertaining to subsets of the data. For example, you might want to know, is A/(A+B) significantly different from 0.5: (i) for Malay, (ii) for Indian, (iii) for Chinese? The overall chi square a...

I believe p.adjust is already used for post-hoc tests *within* particular jamovi analyses such as ANOVA. The difficulty is, how to take pieces of the output (i.e., individual p values) from various separate analyses (a t test here, a chi square there, and correlation from somewhere else) and make th...

In checking some examples in jamovi, it appears that the effect size for the paired samples t test is being computed correctly based on the standard deviation of the difference scores (and nothing to do with pooling). The esci module appears to be doing something else--not calculating the effect siz...

Hi. I think something may be wrong there. A paired t test is equivalent to a one-sample t test on difference scores. Therefore there is only one SD describing the sample of difference scores: There aren't multiple sample-SDs that would need to be pooled. So the concept of pooling shouldn't be applic...

Using jamovi's Rj module you can simply write some R code like: setwd("c:/Temp/") write.csv2(data, "ToothGrowth.csv") Note that write.csv2 writes semicolon-separated values and uses the comma as the decimal character. The resulting file opens properly in Excel when Excel has been...

Just an FYI. You can change Excel's settings so that is uses the dot as the decimal separator:

https://support.microsoft.com/en-us/off ... bb9837bd1e

Hi. Thanks. To fix my example, there is only one item that is to be reverse-scored, and should be represented in my example as a column among several columns: 3243Untitled.png Yes, it ends up not mattering for correlation (reliability) computations because each column is ultimately converted to stan...

Well, my suggestion was just the opposite: Always do the reverse scoring based on the theoretical not the actual range.

RE "The choice of this adaptive method makes sense because the module cannot know the intended scale in advance." 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...