Can I use "simr" package for power analyses on ANOVA models? simr is an R package for conducting power analyses on linear mixed effects models. One might compute power for a model with:
library('simr')
fit = lmer(data=data, formula = x ~ y + (y | z)
powerSim(fit, nsim=200)

My question is this: does it make sense to use this package assess the power of models that were not built with lmer? For example, on a simple ANOVA:
fit2 = aov(data=data, formula=x~y)
powerSim(fit2, nsim=200)

Just to clarify, I know that this CAN be implemented in R (i.e. powerSim(fit2) does not cause an error, and returns output similar to that of powerSim(fit) ), but I'd like to know if using powerSim on an ANOVA model is theoretically flawed.
 A: The article SIMR: an R package for power analysis of generalized linear mixed models by simulation by Green and MacLeod, which is devoted to the simr package,  states the following:


*

*"simr is designed to work with any linear mixed model (LMM) or GLMM that can be fit with either lmer or glmer from lme4. This allows for a wide range of models with different fixed and random effect specifications. Linear models and generalized linear models using lm and glm in base r are also supported, to allow for models with no random effects."

*"Version 1.0 of simr is designed for any LMM or GLMM fitted using lmer or glmer in the lme4 package, and for any linear or generalized linear model using lm or glm, and is focussed on calculating power for hypothesis tests."
Since the help function for the aov function in R states that this function "provides a wrapper to lm for fitting linear models to balanced or unbalanced experimental designs", it makes sense to use the simr package to perform power calculations for tests of hypotheses involving parameters in models which can be fitted with either the aov or the lm functions in R. 
You can find the article here: https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.12504. 
