EJ
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- EJ
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Comments
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Hi kldavids, Sorry for the tardy response -- somehow your post didn't prompt me to respond immediately. I do recall fielding an "El Capitan" question before. So I hope the issue has already been solved. If you want the attention of the JA…
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Hi Papi, This is an interesting approach. I think Jeffreys (1961) also discusses the comparison between two correlations, but I might misremember. Your approach assumes that "q" captures the relevant information in the data -- to the exte…
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Hi Matt, I'll look into this. Basically we use R, but I'll ask the person who coded this to look into this issue specifically. Thanks for pointing it out. Cheers, E.J.
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Hi ESV, Yes, when you design them as nuisance they get added as covariates. This is indeed similar to a hierarchical analyses where you add batches of covariates in a particular order. Cheers, E.J.
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Hi Simon, I'm working on a JASP manual and it will have sections "Example Report". Until that's finished, your best bet is to look at papers that already report Bayesian analyses (such as my own; see my website :-)). Cheers, E.J.
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The paper has a "minor revision from The American Statistician. We've almost completed the revision and I'm pretty confident. But you never know.
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Hi Pat, I've asked the JASP programmers what's up. In the mean time I'd encourage you to post bug reports on the JASP GitHub page -- this is the page that the programmers check. Also, it is the page that most users would consult in case they encoun…
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Hi Tom, Well, if you look at BF10, you see that for every model you have strong evidence in its favor compared to the model without any factors. The full model that includes the interaction is supported (versus the null) more than the model with th…
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It will not be in the next release (scheduled for a week or so after today) but it will probably be in the one after that. I would say it is a few months away. Cheers, E.J.
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Hi Patrizio, This would be an independent-samples t-test. For more information please check out the corresponding video on the JASP YouTube page. Cheers, E.J.
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Hi Matt, JASP borrows most of its functionality from R packages. I have not yet gotten a response from the person who implemented this in JASP, but I'm certain this comes from an R package. And it's nice to hear that it corresponds to what you did …
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I don't think they are available (yet). I will make a note to add them under "descriptives" in a future release. Cheers, E.J.
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Hi Tom, I'm currently working on a paper that explains how to do this. We will post some videos too. These are not available right at the moment, and I'd encourage you to check out this paper: http://www.ejwagenmakers.com/inpress/RouderEtAlinpressA…
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Hi Patrizio, Can you clarify your question, perhaps with a concrete example? Cheers, E.J.
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Hi Ulrike & Kirsten, Together with Ruud Wetzels I once wrote something about partial correlations (http://www.ejwagenmakers.com/2012/WetzelsWagenmakers2012.pdf). This is not in JASP right now and we are exploring alternatives. Yes, the correla…
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Hi Laurent, We are working on a paper that explains the output. Basically, the "effects" output averages across the models. With 0.2 prior probability of each of the five models, the factor "source" occurs in three, meaning a su…
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Hi Zennie, JASP does not do contrasts yet, but I think you should be able to compute what you want using Richard's BF package. I recall Richard also wrote a blogpost on this. Richard may be able to provide the details. Cheers, E.J.
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Hi ksemmelm, We have a similar issue with the Mac, and we are working to resolve it. It is interesting to know that this is also an issue under Windows 7. Of course opening files from within JASP does work, but it is a bug and we will fix it. By th…
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Hi Anna, You can find a preprint on my website: http://www.ejwagenmakers.com/inpress/JamilEtAlGunelDickeyinpress.pdf The paper is "in press" for Behavior Research Methods. Cheers, E.J.
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Hi MSB, (1) The interpretation I gave (50% mass between -x and x) only holds for the Cauchy prior, which is used for the t-test. It does not hold for the beta-star prior, which is used for the correlation test. It is best to just inspect the prior …
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Hi MSB, The best way to understand the shape of the prior is to inspect the plots. A Cauchy prior with of 0.6 still has the center of the mass at zero. When specified as a 2-sided test, this means that 50% of prior mass falls between -0.6 and +0.6.…
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Hi Marieke, Richard may have more to say about this, but the Bayesian test considers the probability of the data under two competing hypotheses about effect size. This automatically takes into account unequal sample sizes. Note that this is also ap…
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Hi Duplex, I would report whatever is consistent with your general mode of inference (classical vs Bayesian). Or report both. All code for JASP is available on GitHub. If you want help to locate the code more quickly I recommend you Email Tahira Ja…
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Hi Duplex, The Bayesian analysis produces a posterior distribution for the log odds ratio. This distribution is induced by the posteriors for the model parameters. You are comparing the result to the outcome of a classical analysis (the classical a…
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Hi Lotje, It seems to me that the second factor explains variance that would otherwise go into your error term. Suppose you study the effect of weight loss for three different diets (the first factor), and the second factor is whether or not partic…
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Hi M, In JASP you can compare models to assess whether inclusion of beta for X2 helps or hurts. However, in case of regression and ANOVA, JASP does not (yet!) return the parameter estimates. Cheers, E.J.
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Hi Lori, About the 2.1 being evidence against the interaction: the table indicated that the two-main effects model didn't do so well against the null model. But adding the interaction didn't help. In fact, it made things even worse: the model with …
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Hi M, The first point is that individual betas only have meaning in the context of a specific model. You can pick the full model, but that's just one (arbitrary?) choice. With respect to your specific question, one easy way would be to plot the pos…
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Hi Lori, First, let's assume that looking at the interaction term is a good idea. Then yes, the BF is 2.1 against including the interaction (over and above the two main effects model). You can get the same result more easily if you use the model sp…
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Hi M, This is on our to-do list. A recent paper on the topic is here: http://sci-hub.cc/10.1016/j.jmp.2015.08.001 I'm not sure whether there is R code, but I expect there is. Cheers, E.J.