Closed AustinLG closed 10 months ago
Hi @AustinLG - can you please provide a reproducible example of a continuous covariate producing an error as a result of being converted to a factor automatically by differentialTest()
? This would help us to understand and troubleshoot your issue. Thanks!
I determined that with more than one continuous covariates and the test method set to "ward", corncob will throw a convergence error. I'm not in a position to share data but simulating two continuous variables and using them with the soil dataset shows it happening. Changing the test method to LRT resolves it.
The key issue here is that the vignette clearly mentions modeling microbial data with continuous covariates in the introduction, but provides no example of the package doing this. Every covariate shown in the vignette is categorical data.
If you're able to share that simulated data, that would help us out. We maintain a lot of software and having specific issues to debug rather than constructing our own saves us time.
I would in general encourage folks to use "LRT" rather than "Wald" anyway. "Ward" probably throws an error anyway, as that's not a name of a test.
Sorry, typo on my part, I intended to say I was using "Wald". Please see my previous comment that the primary issue here is no example using a continuous covariate in the vignette. Adding this to the vignette would be helpful.
Closing this as (1) this is not an issue and (2) I think this abstraction is not sufficiently complex as to warrant a new vignette
Please note that the current vignette on CRAN, linked here states that it includes examples for continuous covariates, but no such example is provided. I have yet to see an example of corncob used with continuous covariates and would very much like to see this. At present, it appears any numeric integer covariate provided to differentialTest() is considered as a factor and the many levels this introduces produces a convergence error.