EJ
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- EJ
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Comments
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a) Yes you can do this, especially when you use informed prior distributions. The null divides out so you are left with a direct comparison between two instantiations of H1. b) This is a little tricky in this specific case. I suggest that your quest…
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I've passed this on, we'll be in touch! E.J.
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Hi Matthew, I am not quite sure what you mean with "muting" -- do you mean filtering? Or are you using the dataMode/SKF version and are you in data editing mode? A screenshot would help! Cheers, E.J.
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Hello Tong, You might try and turn on "Safe Graphics" in the Preferences. Please let me know whether that worked. If this does not work, please post your issue on our GitHub page so the programmers can deal with it. The download page has a…
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Yes, I agree with eniseg2. Sorry about my tardiness, I am a little busy at the moment -- hope to be back up to speed soon. Cheers, E.J.
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Sounds like a great idea! We'll add you to our worldmap if you aren't already on there. Could you post this feature request on our GitHub page? (for details see https://jasp-stats.org/2018/03/29/request-feature-report-bug-jasp/) I am sure we can inc…
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But you need Log(eyes + 1), right? So the log should go over "eyes+1"
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What is the log1eyes transformation? It is not log(1+eyes)...can you make a screenshot of the transformation rule you applied?
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Dear Haizeydays, Which values are infinite when you transform them? Do you have a screenshot? Cheers, E.J.
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I think this does make sense; you could make this a feature request on our GitHub page (for details see https://jasp-stats.org/2018/03/29/request-feature-report-bug-jasp/) Cheers, E.J.
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By adding more levels H1 becomes relatively more complex. The same happens when you quantify evidence for the null in case of data from a fair die. You can either analyze odds vs evens or analyze the uniformity across all categories. H0 will be more…
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I'll forward this to Koen, our expert for this analysis E.J.
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Yes, you can achieve this using the "edit image" option! See https://jasp-stats.org/2021/09/21/introducing-jasp-0-15-new-languages-basic-plot-editing-raincloud-plots-and-more/ Cheers, E.J.
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Right now JASP does not do imputation. We have it under development but it will take a while to get there. Without imputation you'd simply remove the incomplete cases -- not sure what else you could do. Cheers, E.J.
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Si se refiere a la invariabilidad de la medición, le sugiero que utilice nuestra funcionalidad de modelado de ecuaciones estructurales (lavaan). Ayuda a proporcionar un ejemplo concreto. (traducido con DeepL)
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Dear LuCA, Sorry for the tardy response. Indeed, 0.5 in the ANOVA maps on to 0.707 in the t-test, if I recall correctly. You can try this out by taking t-test data and analyzing it with an ANOVA. The problem with prior distributions that are overly …
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I'll forward this to our network experts... E.J.
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Note that for sensititivy/specificity and the like JASP offers the "binary classification" functionality, see https://jasp-stats.org/2021/09/28/binary-classification/ Cheers, E.J.
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Hello DrPRW, You can use the "compute new columns" functionality to center the variables. Maybe we ought to make this even easier. I am a little surprised that centering the variables would help actually. Johnny/Don? Wrt the link you gave:…
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This issue has been picked up in a different thread. E.J.
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I'll attend our network experts to this! Cheers, E.J.
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Thanks for the suggestion. It's on our radar! E.J.
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Dear Marti, Thanks for reporting this, I'll bring it to the attention of the programming team. Note that bug reports such as these can be issued directly through our GitHub page (https://jasp-stats.org/2018/03/29/request-feature-report-bug-jasp/) an…
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In that case I'd add the main effects to the null model as nuisance factors, so they are always included (under "model").
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I'll forward this issue to our SEM expert. E.J.
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The book can be found at https://nl1lib.org/. I'll forward this issue to our ANOVA expert. We ought to mention something about this in the help file... Cheers, E.J.
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I don't think so. It would be a good feature request for our GitHub page (see https://jasp-stats.org/2018/03/29/request-feature-report-bug-jasp/) Cheers, E.J.
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I completely agree. This would be a good feature request for our GitHub page (for details see https://jasp-stats.org/2018/03/29/request-feature-report-bug-jasp/) This way the request will not be forgotten. Cheers, E.J.
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Clearly an important issue, as this is a popular analysis. However, I recommend you post this as an issue on our GitHub page, as it will require the attention of the programming team. For details see https://jasp-stats.org/2018/03/29/request-feature…
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You mean when you do multiple t-tests? This is essentially how the post-hoc ANOVA tests work: they are the result of combining a t-test Bayes factor with a correction term that depends on the number of tests that are conducted. Cheers, E.J.