andersony3k
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A proportion test is restricted to 2 X 2 out of logical necessity. When the table size is 2 X 2, "contingency" is translatable to "differences between two proportions. That's not the case for tables larger than 2 X 2. For those large …
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If you really have the "whole population," such that you're not trying treat the data you have as a random sample, and not trying to draw inferences about a larger set (a population), then descriptive statistics (means, medians, totals, et…
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While there could be an error in the Bayesian repeated measures routine, here's another possibility: It's known that JASP's "Bayesian repeated measures" routine doesn't actually perform a repeated measures analysis. Instead, it performs a …
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By the way, why is the directory called "JAPS" and not JASP?
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gvt. Again . . . Just because the data/residuals are significantly non-normal and the variances are significantly unequal doesn't necessarily mean the violations are large enough to matter. Some judgment is required to make those determinations…
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I believe you've already discussed this question and gotten some answers in other threads and forums.
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fyi: https://forum.jamovi.org/viewtopic.php?t=2731
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I wonder, what is the result of a frequentist repeated measures ANOVA on the same data? Does it still produce an incongruence between main effect and post hoc?
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Could there be any rows with missing data that are excluded from the ANOVA but (incorrectly) included in the post hoc test?
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Could there be assumption-violations? It's difficult to tell what might be going on without seeing the actual data.
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I'm unclear as to the study's design. For example, you indicate the first column codes "condition" (in; out) varying across rows, but your graphic indicates that condition varies cross columns rather than across rows. So, to be be of assi…
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Actually, I don't have an answer. I meant to write: > I believe that multiple regression is all about > assessing relationships between variables > while having "partialled out" some other variable > or set of var…
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I believe that multiple regression is all about assessing relationships between variables while having "partialled out" some other variable or set of variables. So I think you'll be fine if you're willing to shift your question to somethin…
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But presumably the study was not designed to have "40" in one group and "35" in the other. Instead (presumably) that's just how many happen to have been sampled from each of the two categories. Therefore neither the row counts n…
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If Bayesian contingency table analysis is to be used, then in order for it to be "Independent multinomial sampling" as described in the JASP manual, for one of the two variables, an equal number of individuals would need sampled from each …
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The manual at http://static.jasp-stats.org/Manuals/Bayesian_Guide_v0_12_2_1.pdf describes how to tell JASP what sampling plan you've (already) used to collect your data. The relevant text is copied below. Thus, from what you've described, it appears…
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It sounds to me that you want to assess a "2X2" "contingency." If that's the case then the appropriate Bayesian analysis in JASP would be: "Frequency"/"Bayesian"/"Contingency Tables".
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It's my impression that in Bayes' Theorem, all of the information pertaining to prior beliefs is contained in the 'prior odds' term. I contrast the Bayes factor likelihood ratio is only bout the current data. So I think that any conceptualization of…
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@EJ Thanks EJ. I did not know that for typical statistical scenarios--where the alternative hypothesis is a diffuse set of non-zero effect-size possibilities--the statement from the JSP manual, that "Posterior odds Posterior odds = Bayes facto…
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I believe that the "prior" options in JASP are not options that allow the user to specify prior odds that are different from 1/1. Instead, you should do the following . . . If (for example) Study 1 yields BF[10] = 2.3, and Study 2 (a repli…
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My understanding is that normally you should look at the Bayes Factor from Study 1 and multiply it by 1/1 if the prior odds of the alternative versus the null hypothesis were 1/1 {50/50}. This yields the posterior odds (which is of course identical …
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Compute the sum of 5, 9, and 10. (Answer = 24). Compute a new column, C, consisting of: 5/24; 9/24; 10/24. Compute a final column, D = A*C. Compute the sum of Column D.
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@EmilieC I definitely would call myself a non-expert in Bayesian analysis, especially concerning complex linear models. Of course, even non-experts like myself need sometimes need to make scientific/statistical judgments that go a bit beyond our exp…
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JASP's machine learning module supports networks with arbitrary numbers of hidden layers. (Note: A "perceptron" is a historical example of a neural net.)
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Also, if you want to compare Bayesian RM ANOVA to something frequentist, you should compare it to a frequentist linear mixed-effects model since, I'm told, JASP's Bayesian "repeated measures ANOVA" is really a Bayesian Linear Mixed-Effects…
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I don't know the answer to your question, but apparent inconsistencies like the one you're seeing lead me to adopt a general practice trusting simpler Bayesian analyses (e.g., t tests) more than complex ones (e.g., ANOVAs).
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Hi. "Two-way interaction" means the same thing as "1st order interaction" (though I believe the former term is more commonly used). "Three-way interaction" means the am thing as "second order interaction." I…
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I think your use of the term "hierarchical" has a completely different meaning than "hierarchical data" in statistics. An example of hierarchical data would be if age group could be young or old in the 40-40 condition but was re…
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Hi. It's still ambiguous whether you have Gender factor (male; female) or a Gender Correspondence factor (different; same). I'll assume the latter. Likewise, it's not clear whether your talking about an Age Category factor (young; old) or an Age Cat…
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I agree with pchs0114 except that if there are really only two individuals, it's not worth doing any kind of statistical test. Two is not enough to be convincing.