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Summarise fixed effects from fitted models

Source: R/summarise_gazepoint_fixed_effects.R
summarise_gazepoint_fixed_effects.Rd

Create a compact manuscript-ready fixed-effect summary table from common models used in gp3tools workflows.

Usage

summarise_gazepoint_fixed_effects(
  model,
  model_name = NULL,
  conf_level = 0.95,
  exponentiate = FALSE,
  drop_intercept = FALSE
)

Arguments

model

A fitted model object, or a gp3tools fit object containing a $model element.

model_name

Optional model label used in the returned table.

conf_level

Confidence level for Wald confidence intervals.

exponentiate

Logical. If TRUE, exponentiate estimates and confidence intervals. This is useful for logistic models when reporting odds ratios.

drop_intercept

Logical. If TRUE, remove the intercept row.

Value

A tibble with fixed-effect estimates, standard errors, test statistics, p-values when available, confidence intervals, significance stars, and status fields.

Details

The function supports lm, glm, lme4 mixed models, and mgcv GAM/BAM objects. It can also accept a gp3tools fit object containing a $model element. Confidence intervals are computed using a Wald approximation from the estimate and standard error so that the function remains lightweight and fast for mixed models.