Issue with Documentation

[savindi-wijenayaka]

1. Description

1. The documentation and functionality don't align with each other in GLMM models.
2. No description or links to the acceptable methods for certain parameters.
3. The alignment between the R class and the Python class is not clear.

2. Minimal reproducible example

Each issue above is described in detail below:

1. Check the documentation on GLMM estimation method. The conf_method default is wald in the method description but parametric in the parameter description. Moreover, ddf_method is a parameter in the parameter description but not in the method description.
2. I want to use the Markov chain Monte Carlo (MCMC) or nonparametric bootstrap confidence intervals to get the CIs, if possible. Keyword argument to use for this seems to be the conf_method, however, accepted values ("wald", "normal", "residual", "ml1", "betwithin", "satterthwaite", "boot", "profile", or "uniroot") has no record of what they are in the documentation. I assume boot is for nonparametric bootstrap confidence intervals? Also, the default value for the conf_method seems to be parametric according to the summary report. But what does parametric mean? Also, if I try to pass the value parametric to the conf_method, it throws an error saying it is not an option, which is very weird given that the default is parametric.
3. I would also like to know which method is being used for the fitting. Are we using the Laplace approximation? According to the R documentation, we can specify nAGQ parameter to change the Laplace approximation to the Gauss-Hermite approximation? Is it possible to do this in Pymer4?

3. Version

pymer4 version=0.9.2 build=2f5b405 channel=ejolly