<p>Yes, I think it is, though you may encounter people (and they could be reviewers) that find this somehow objectionable, and you will need to be familiar enough with both approaches and prepared to defend your choices if they are questioned. Be aware of your readership: if these approaches are common in the journal(s) you submit to, don't worry, but if they are not you may need to spend more time/space in your paper explaining them.</p>
<p>Here's a paper that might help with support, I'm sure there are many others:</p>
<p><em>Bayarri, M. J., &amp; Berger, J. O. (2004). The interplay of Bayesian and frequentist analysis. Statistical Science, 19(1), 58-80.</em></p>
<p><a href="https://www2.stat.duke.edu/%7Eberger/papers/interplay.pdf" rel="nofollow noreferrer">https://www2.stat.duke.edu/~berger/papers/interplay.pdf</a></p>
<p>One caution for something that would <em>not</em> be acceptable (which is not something you've proposed) would be first trying out a frequentist approach, discovering your results are &quot;not significant&quot;, and then using Bayesian approaches to make pseudo-frequentist arguments about something that sounds a lot like statistical significance. That would be a form of &quot;p-hacking&quot;.</p>

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2024-08-05T13:25:55.057Z
2024-08-05T16:08:37.693Z
2024-08-05T16:08:37.693Z
Bryan Krause
<p>I'm writing a paper for a fairly generic psychology journal. Initially, I planned to use only frequentist methods for my analyses. However, I found that the nlme package I was using for regression analyses was unable to apply parameter bounds in the way I needed. So I switched to the brms package, which allowed me to set priors on each parameter in the regression analyses, effectively constraining the parameters in the way I was hoping to achieve with nlme.</p>
<p>I'm concerned about whether it's acceptable to mix frequentist and Bayesian methods in the same paper, especially if they are used for different analyses. Essentially, I’m using frequentist methods for my basic descriptives, and Bayesian methods for the more complex regression analyses. As long as I explain my approach clearly, is this practice acceptable?</p>

<statistics><analysis><bayesian>
Is it acceptable to mix Bayesian and frequentist analyses in the same article?
Piethon
# Is it acceptable to mix Bayesian and frequentist analyses in the same article?

(Asked by: username_0 on 2024-08-03)

I'm writing a paper for a fairly generic psychology journal. Initially, I planned to use only frequentist methods for my analyses. However, I found that the nlme package I was using for regression analyses was unable to apply parameter bounds in the way I needed. So I switched to the brms package, which allowed me to set priors on each parameter in the regression analyses, effectively constraining the parameters in the way I was hoping to achieve with nlme.

I'm concerned about whether it's acceptable to mix frequentist and Bayesian methods in the same paper, especially if they are used for different analyses. Essentially, I’m using frequentist methods for my basic descriptives, and Bayesian methods for the more complex regression analyses. As long as I explain my approach clearly, is this practice acceptable?

**Tags:** statistics, analysis, bayesian


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## 1 answers

### Answer by username_1 on 2024-08-05. Score: 2 | Accepted answer

Yes, I think it is, though you may encounter people (and they could be reviewers) that find this somehow objectionable, and you will need to be familiar enough with both approaches and prepared to defend your choices if they are questioned. Be aware of your readership: if these approaches are common in the journal(s) you submit to, don't worry, but if they are not you may need to spend more time/space in your paper explaining them.

Here's a paper that might help with support, I'm sure there are many others:

*Bayarri, M. J., & Berger, J. O. (2004). The interplay of Bayesian and frequentist analysis. Statistical Science, 19(1), 58-80.*

[https://www2.stat.duke.edu/~berger/papers/interplay.pdf](https://www2.stat.duke.edu/%7Eberger/papers/interplay.pdf)

One caution for something that would *not* be acceptable (which is not something you've proposed) would be first trying out a frequentist approach, discovering your results are "not significant", and then using Bayesian approaches to make pseudo-frequentist arguments about something that sounds a lot like statistical significance. That would be a form of "p-hacking".


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