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We also evaluated the sensitivity of our inferences by testing different priors.
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We tested different priors, and the posterior probabilities were reasonably robust (Additional file 1: Table S3).
You can only know that by testing the different options.
Also, test different creatives.
We thus attempted to test the sensitivity of the results by using different priors and our results showed that the pooled effect size is not sensitive to the priors used.
Further model evaluation can be conducted by testing the sensitivity of the results to various different prior distributions [ 53].
Prior to implementing the models, we assessed possible overdispersion of the count outcome data by testing whether the negative binomial dispersion parameter was significantly different from zero.
Now, we consider different priors.
We tested priors with different accuracy, i.e. different levels of agreement with the true network.
Finally, we fit additional models to test the sensitivity of our results to different prior specifications.
We examined this approach prior to testing the different WGA options.
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