Plot Treatment Means Across Models

Compares observed and predicted treatment means across multiple fitted models for a selected treatment.

Usage

plot_treatment_mean(..., treatment, show_se = TRUE)

Arguments

...

Fitted model objects.

treatment

Treatment name.

show_se

Logical. If TRUE, displays a standard-error ribbon around the observed treatment mean.

Value

A ggplot2 object.

Details

The observed treatment mean is displayed as a black line with optional standard-error bands. Predicted treatment means from each fitted model are overlaid for visual comparison.

This visualization is useful for:

• Comparing competing kinetic models

• Evaluating treatment-level model performance

• Assessing agreement between observations and predictions

• Comparing fermentation dynamics among models

See also

plot_all_treatment_means, compare_models_by_treatment, fit_groot, fit_gompertz

Examples

files <- example_data()

raw_data <- read_ankom(
  files$ankom
)

metadata <- read_metadata(
  files$metadata
)

gp <- process_ankom(
  raw_data,
  metadata,
  headspace_ml = 210,
  temperature_c = 39
)

groot_fit <- fit_groot(
  gp
)
#> Warning: Large negative pressure values detected. Minimum PSI = -1.274 . Please inspect the affected bottles.
#> rumenGP data validation passed.
#> Observations: 1752
#> Heads: 24
#> Treatments: 5

gompertz_fit <- fit_gompertz(
  gp
)
#> Warning: Large negative pressure values detected. Minimum PSI = -1.274 . Please inspect the affected bottles.
#> rumenGP data validation passed.
#> Observations: 1752
#> Heads: 24
#> Treatments: 5

plot_treatment_mean(
  Groot = groot_fit,
  Gompertz = gompertz_fit,
  treatment = unique(
    gp$Treatment
  )[1]
)