parameters 0.26.0

Changes

• The effects argument in model_parameters() for classes merMod, glmmTMB,
  brmsfit and stanreg gets an additional "grouplevel" option, to return
  the group-level estimates for random effects.

• model_parameters() for Anova-objects gains a p_adjust argument, to apply
  p-adjustment where possible. Furthermore, for models from package afex, where
  p-adjustment was applied during model-fitting, the correct p-values are now
  returned (before, unadjusted p-values were returned in some cases).

• Revised code-base to address changes in latest insight update. Dealing with
  larger models (many parameters, many posterior samples) from packages brms
  and rstanarm is more efficient now. Furthermore, the options for the
  effects argument have a new behaviour. "all" only returns fixed effects
  and random effects variance components, but no longer the group level
  estimates. Use effects = "full" to return all parameters. This change is
  mainly to be more flexible and gain more efficiency for models with many
  parameters and / or many posterior draws.

• model_parameters() for Anova objects gains an include_intercept argument,
  to include intercepts in the Anova table, where possible.