Dmartin427
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Thank you, EJ! You were just the man I was hoping would respond when I made this thread. I'll dig into your works now, and I appreciate the fast response.
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I had this exact nightmare of interpretation when I was building an advanced research statistics course for my health science students. Long story short, the interpretation of the coefficient signs are the opposite of what you would initially expect…
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Katie, They look fine to me - your upper CIs are higher numbers than your lower CIs, at least as far as I can tell. The only point of confusion I can see is that the upper CI is reported before the lower CI, which is unusual (at least for us USA guy…
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Yes, you're interpreting it correctly! In the estimate plot, the y-axis shows the predicted probability of survival (P(Survived = 1)) for each passenger class (PClass). So, a passenger in 1st class has about a 0.75 (75%) chance of surviving, which m…
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Classically, you'd consider a generalized linear model with the appropriate family and link, depending on the distribution associated with your non-normally and heteroskedasticity. You could also, in the event of heteroskedasticity, use the bootstra…
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May I recommend going into Descriptive Statistics --> Customizable Plots --> Boxplots (in colorblind color palette) to address all of your concerns in one fell swoop?
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Sounds like a binomial test will do exactly what you need, which you can find under "Frequencies --> Binomial Test" on the ribbon bar along the top of your JASP window. Just drag and drop each variable (e.g. First Class, Fifth Class, Ma…
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I've published papers with multinomial tests and contingency table tests where the Bayes Factor was infinity, so no, this is pretty reasonable. Considering the practically perfect linear relationship between Bayes Factors and p-values, you can rest …
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To put it plainly: The purpose of the Bayesian Binomial Test is to assess the probability that two independent nominal variables have counts that are either different from an expected value (BF10), or the same as an expected value (BF01). In other w…
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Thank you, patc3! I'll start using your shortcuts moving forward - I appreciate it!
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drravikch, You can use the JASP Distribution module to check the fit of a given variable to all kinds of distributions. However, the utility of this may depend heavily on your familiarity with the topic of distributions. In any regard, unless JASP s…
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Hey Rachel! Here's how I usually do it in JASP: Run your ANOVA as a Linear Regression instead. Just put your DV in the DV box, and then your grouping variable in the Factor box. Go to the Statistics dropdown below, and check the Append Residuals to …
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Although I am not the authority on it, here's how I do it in JASP: Run your ANOVA as a Linear Regression, with your DV in the DV box and your groups in the Factors box. Go to the Statistics dropdown, and then look towards the bottom for the Append R…
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It does indeed! If you go into Generalized Linear Model under Regression, and then set the family to Other, you can pick between Multinomial, Ordinal and Firth Logistic Regression. https://forum.cogsci.nl/uploads/143/4L3GB2PU0QEZ.png The output for…