Timeline for Bayes-factor for testing a null-hypothesis?
Current License: CC BY-SA 3.0
5 events
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| Feb 3, 2014 at 10:31 | comment | added | richarddmorey |
So, if I understand, you could define $\alpha_{ci} = \mu + \gamma_c + \delta_i + \epsilon_{ci}$ where $c$ indexes conditions, $i$ indexes participants, and $\mu$, $\gamma$, and $\delta$ are the effects of the grand intercept, condition, and participant, respectively? If that's the case, you can use the BayesFactor package. You can email me for further help if you like. You'll use generalTestBF().
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| Jan 29, 2014 at 13:02 | comment | added | thias | what I meant in my previous comment, that I would like to compare the group-level posterior distributions from a hierarchical bayesian model. Say that my model is built such that the $i$'th subjects $\alpha_{med,i}$ and $\alpha_{ctrl,i}$ parameters are distributed according to a normal distribution with mean $\mu_{\alpha_{med}}$ vs. $\mu_{\alpha_{ctrl}}$, how can I compare the posterior distributions for $\mu_{\alpha_{med}}$ vs $\mu_{\alpha_{ctrl}}$? These posterior are defined by their MCMC samples, so just comparing samples with t-test does not seem to be reasonable? | |
| Jan 28, 2014 at 20:15 | comment | added | richarddmorey | The BayesFactor package implements Bayesian Linear Mixed Effect models. If you're happy living with the assumptions of that class of models (linear effects, independent normal error terms) then you can use the package. I can't say much more without knowing your application. | |
| Jan 28, 2014 at 8:36 | comment | added | thias | thanks for the link. As far as I can tell, the bayesfactor package implements a bayesian t-test which takes two samples as input. While I could do this on the subject-level, I would also be interested in directly comparing the group-level estimates from the hierarchical model. Is this possible using this package, too? | |
| Jan 26, 2014 at 19:20 | history | answered | richarddmorey | CC BY-SA 3.0 |