Symbolize an lme4 lmer() fit (Gaussian, v0.10 first slice)

Builds a symbolized_model from an lmerMod object. v0.10 covers the Gaussian conditional submodel with optional (1 | g) random intercepts. Generalised mixed models (glmer / glmerMod) are routed through symbolize.glmerMod.

Usage

# S3 method for class 'lmerMod'
symbolize(
  fit,
  symbols = NULL,
  units = NULL,
  context = NULL,
  ci_method = "Wald",
  ...
)

Arguments

fit

A fitted statistical model object.

symbols

Optional named character vector mapping variable names to user-supplied LaTeX symbols, e.g. c(body_mass = "W_i", temperature = "T_i").

units

Optional named character vector mapping variable names to units, e.g. c(body_mass = "g", temperature = "C").

context

Optional short character description of the model, e.g. "avian body-size location-scale model".

ci_method

Confidence-interval method passed to lme4::confint.merMod. One of "Wald" (default, fast), "profile", or "boot".

...

Reserved for method-specific extra arguments.

Value

A symbolized_model object.

Confidence intervals

CIs come from lme4::confint(fit, parm = "beta_", method = ci_method). Default ci_method = "Wald". Profile-likelihood CIs ("profile") are slower but more honest for fits with small group counts. ci_method is stored on metadata as lowercase "wald" / "profile".

References

Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1-48.