patc3
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Did you fix your problem yet? If not, I suggest you file a ticket on GitHub, the dev team is generally pretty responsive: https://github.com/jasp-stats/jasp-issues/issues/new?template=bug-report.yml (you need a free GitHub account) If you've updated…
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There's several contrasts/post-hoc comparisons that might be of interest to you, notably: under Contrasts, you can pick "custom" and enter your own contrast coefficients (I think this is what you're looking for) https://forum.cogsci.nl/upl…
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I think if you just change the "Value" entries manually to 0 and 1 instead of Male and Female, it might work
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I think some of the comments here might help: https://forum.cogsci.nl/discussion/9659/how-to-transform-a-new-variable-in-jasp#latest
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Previous versions are available here: https://jasp-stats.org/previous-versions/
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hey it just occurred to me, you might not need the last for loop at all if you run in R, for example just this model string This still doesn't run in JASP and I think it's because where you can say variable.names="x" in coda.samples(), JAS…
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By the way if you wanna check that the two models are approximately the same you should try with a LOT more missing data, e.g. nmiss=700 (or something extreme like that). You stand more chance of spotting a difference between the two models (if ther…
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Hi Jonathan, you're very resourceful, yes I think conceptually this should be the same. Nicely done. Also it's a nice guess what you said about NAs, I don't know why it fails in JASP but it's a good guess.
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Well, you're right that it runs in R but not in JASP, not sure why yet... this is the error I get (missing data go from x[991] to x[1000]) https://forum.cogsci.nl/uploads/959/G39EYMTFP0TS.png
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why do you say it works in rjags but not in jasp? would it be possible to give the R code to run rjags as well so I can compare? I can see it doesn't work in JASP
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Currently I doubt this is possible. Also some fields use different alpha values (cutoffs to declare significant) so I assume it would need to be customizable. You could make a feature request here: https://jasp-stats.org/feature-requests-bug-reports…
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If you're talking about cells resulting from a chi-square test (seeing as you're mentioning contingency tables in the title), then standardized (adjusted Pearson) residuals are interpreted as z scores, which carry no degrees of freedom. A z test is …
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You can change preference for number of decimals in settings. You could set it to 0 or 1, the analysis will reload, and you can later re-change the setting if you want (mine is set to 3 decimals) https://forum.cogsci.nl/uploads/923/XIJGM317B6II.png
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Yes there is a module you can add by clicking the blue plus sign in the right corner: https://forum.cogsci.nl/uploads/847/64W4JHH8NLQ0.png https://forum.cogsci.nl/uploads/102/68YSUJRJC9KG.png https://forum.cogsci.nl/uploads/287/MA5LI4XIAK12.png
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You can do summary(lmm) to look at the output, and if you want all pairwise comparisons between your conditions, you can do: library(emmeans) emmeans(lmm, pairwise~Condition, adjust="none") To be able to use emmeans you will have to use th…
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Within JASP you have a couple of options, one is simpler the other one is more involved (though neither is simple, unfortunately). Taking the example of repeated measures and modeling change over time, the first option is to use the R console module…
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The default is identity, and I'm guessing it's difficult to change it, because the R library that JASP uses in the backend (lme4) is quite limited in terms of covariance structures. What type of covariance structure were you hoping to use?
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Surely you need raw data (it looks like you're trying to run the analysis on summary data, either that or you have only 4 observations)
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In case it helps, some analyses already allow weighting, e.g. linear regression: https://forum.cogsci.nl/uploads/238/EBQ554GS784Q.png Generalized linear model: https://forum.cogsci.nl/uploads/751/QP12OQZ1QYVJ.png
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@TarandeepKang hi Tarandeep, to me this doesn't seem like time well invested, I've personally never actually used hierarchical regression outside of classes, and I do this for a living. Just my 2¢
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After some testing, I think you can reproduce this using these steps: 1) add all your variables (first and second block) as your predictors https://forum.cogsci.nl/uploads/540/Q1OUP8LMFZUA.png 2) under "Model", enter the variables from y…
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Does this not do what you want? It's in the hamburger menu under Open -> Database https://forum.cogsci.nl/uploads/506/HVUO8GJKCAAT.png
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When you wonder about an analysis input, you can look up the documentation for this specific analysis by clicking the little "i" (info) button: https://forum.cogsci.nl/uploads/744/Q883OG4HH02T.png In this case the documentation indicates t…
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Under the "Statistics" menu where you checked confidence intervals, you can also check "Odds ratio scale": https://forum.cogsci.nl/uploads/086/8PPD1BW3X0CG.png
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yes the latter (to get the OR, you take the exponential of the estimate) You can take the exponential of the lower and upper limits of the CIs if they're based on estimates and they'll become odds ratios
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To put it simply, you can say things like we're 95% sure that the parameter (e.g. regression coefficient) is between <lower> and <upper>, or there is a 95% chance that the parameter is between <lower> and <upper>. The reality…
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Don't add paths from controls to IV, only to mediators and outcomes (here it fails because your IV is categorical). Age and mschool shouldn't predict NEGFAMDI (that's your IV right?)
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To make parameters appear in the "Parameters in model" you need to click ctrl+enter to apply the model you wrote. Yes it's possible in both JAGS and Process. Why do you prefer JAGS? Here's the setup using the Process module (1 predictor = …
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Equivalently you can also specify this using paths (no need for Hayes model numbers): https://forum.cogsci.nl/uploads/678/7Y4RKGPZRXHD.png
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Wow you're right, I hadn't realized Bayesian had been implemented in Process. Here's how I replicated the analysis: https://forum.cogsci.nl/uploads/767/IYWSNSLDQZBR.png https://forum.cogsci.nl/uploads/217/MA48FUTK55AS.png