andersony3k
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Yes, that's right.
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Hi. I don't think you'll find a standard, straightforward way to do inferential statistics on the frequencies of NON-mutually-exclusive categories. You could filter your data to include only those children whose answers fell in one and only one of t…
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Select FREQUENCIES, CONTINGENCY TABLES. Make one of your fixed factors the ROW variable. Make the other your COLUMN variable. I think you will see that some cells in the table are missing in that they have a frequency of 0.0. That's not allowed in A…
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I think a rank-based analysis is fine in these situations as long as one doesn't treat the test as going beyond ranks in any way. The statistical inference concerns whether, in the population, the Group A values tend to rank differently (i.e., highe…
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@EJ OK. But maybe the situations in which you need non-parametrics the most are when such a transformation is not possible because the two non-normal distributions have different shapes (as illustrated below). https://forum.cogsci.nl/uploads/846/PK…
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@JohnnyB Thanks. From the paper, I'm seeing that the latent-normal assumption applies when you have ranked data that might well have been normal had they not been converted into ranks. However, I believe a major motivation for performing a Mann-Whit…
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Also, in JASP as well as any other standard stats package I can think of, the RM ANOVA algorithm does not accommodate missing data. For example, if you have . . . subject#1 trial #1 = 39 subject#1 trial #2 = 33 subject#1 trial #3 = 47 subjec…
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My recollection from doing RM Measures ANOVA in SPSS is that SPSS always produced univariate output along with multivariate output, and the results for the univariate approach were always identical to the results for the multivariate approach.
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Fisher's z = .5 ( NaturalLog[1 + r] - NaturalLog[1 - r] ). So you need to do the Fisher's z transformations after you've used JASP to compute the correlations.
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I suspect that you would have to employ programming skills to create your own, custom version of JASP. The code is here: https://github.com/jasp-stats/jasp-desktop
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Best to wait for the expert to return. However, in playing around with some numbers, it's clear to me that the median 'effect size' in the posterior plot is not the median rank-biserial correlation. This is because notice that the median 'effect siz…
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Maybe you somehow messed up the data in the JASP file? With JASP, I get 0.965. See below. https://forum.cogsci.nl/uploads/284/XQR41QBC0JZ6.png
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Distinct from the issue of statistical power is the question of whether you can demonstrate that you didn't capitalize on chance by halting data collection as soon as you found a sufficiently-extreme Bayes factor to warrant a clear inferential stati…
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Hi Dexterama. I think you should not expect the ANOVA results to be compatible with the ANCOVA results, since the two types of analyses ask and answer different question. Specifically, each ANCOVA draws the following type of conclusion. "Had I …
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It only elongates the x axis (It does not distort text, etc). Initially it looks like everything is stretched, but that fixes itself in a few seconds. https://forum.cogsci.nl/uploads/519/A7E8B609TPI3.png
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For the single plot, you can drag the little triangular handle (that appears below the figure) to the right, to elongate the x axis. (Note: The last time I checked, this action produced a temporary rather than lasting change. That is, if you save an…
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This is just a side comment: If I were reviewing a paper, and if the main effects and interaction results depended on the ordering of the entered terms, I'd be uncomfortable with that. I'd also want to see an analysis (e.g., a regular old rmANOVA) i…
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Actually, in JASP (0.18.3), I haven't found a way to edit/scale-change any of the scatter plots of the raw data, however they're produced (they're all complex, 'customizable' even if they aren't labeled as such). The closest I've come is to produce …
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JASP will give you all of the pairwise comparisons at the same time, if you're willing to accept what many people regard as the correct approach, which is to always use pooled variances.
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Actually, I think there's a legitimate question concerning the unpooling of error-terms. In an ANOVA, there's an assumption of equal error variances. Likewise, for repeated-measures, there's an assumption that the variance of the difference scores i…
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Regarding the after-versus-follow-up comparison in the control condition: Another reason the two ANOVAs produce different post-hoc results is that error term (i.e., variance(s)) for each comparison is estimated from the entire data set--not just fro…
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It's difficult to tell from the screen shots since, in JASP, the repeated-measures cell fields don't always show the entire column name. Maybe you entered the same column name (NI_RT_Forced_...) in two separate fields? Somehow JASP isn't able do fin…
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I think there can also be issues with Type I error inflation if some interactions (or other components) are excluded from the model.
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I think it's quite common for the user to want a 'repeated-measures-ANOVA-like' result, which would include all possible interactions. Thus, even if the default were to exclude interactions, there would still be the question of whether JASP is runni…
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Correction: Chi Sq = Sum_for_Each_Cell [ ((Observed_Count - Expected_Count)^2) / Expected_Count ]
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I'm pretty sure that's the way Chi Square contingency is supposed to work. For each cell, the expected count = (row_total * column_total) / grand total. Thus, the expected count will be zero if either the row total or the column total is zero. Howe…
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@johndavid2 What is a large language model? :-)
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If you run a repeated-measures ANOVA with and without corrections for sphericity violation, you'll see that the corrections do not impact the post-hoc tests. There's nothing more to be done, since the question of sphericity doesn't apply to a repeat…
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I believe you've identified a limitation in JASP that tends not to be present in other stats programs.