Plotting Principles
The original book uses simple black-and-white plots. In R, ggplot2 can recreate the same scientific comparisons with clearer labels and reproducible code. The goal is not decorative plotting; it is to show design structure, grouping, and model implications.
Split-Plot Packed Cell Volume Data
ex124_plot <-
ex124 |>
collapse::fmutate(herd = factor(herd))
ggplot2::ggplot(
ex124_plot,
ggplot2::aes(x = herd, y = PCVdif, shape = dose, color = drug)
) +
ggplot2::geom_point(size = 2.4, position = ggplot2::position_jitter(width = 0.08)) +
ggplot2::facet_wrap(~ drug, nrow = 1) +
ggplot2::labs(
x = "Herd",
y = "Change in packed cell volume",
shape = "Dose",
color = "Drug",
title = "Packed cell volume response by herd, drug, and dose"
) +
ggplot2::theme_minimal()
Region, Drug, and Dose Means
ggplot2::ggplot(
ex125,
ggplot2::aes(x = dose, y = Pcv, group = Drug, color = Drug)
) +
ggplot2::stat_summary(fun = mean, geom = "line") +
ggplot2::stat_summary(fun = mean, geom = "point", size = 2.6) +
ggplot2::facet_wrap(~ Region) +
ggplot2::labs(
x = "Dose",
y = "Mean packed cell volume",
title = "Mean response by region, drug, and dose"
) +
ggplot2::theme_minimal()
Longitudinal PCV Data
ggplot2::ggplot(
ex33,
ggplot2::aes(x = time, y = PCV, group = animal_id, color = breed)
) +
ggplot2::geom_line(linewidth = 0.5) +
ggplot2::geom_point(size = 1.4) +
ggplot2::labs(
x = "Time",
y = "Packed cell volume",
color = "Breed",
title = "Longitudinal packed cell volume by animal"
) +
ggplot2::theme_minimal()
Model-Based Lines for Example 3.1
The book displays fitted lines for Example 3.1 Model 3. The packaged ex31 data can be plotted with simple group-specific linear fits to inspect the same relationship between baseline PCV and one-month PCV.
ex31_plot <-
ex31 |>
collapse::fmutate(
treatment = ifelse(drug == "BERENIL", paste(drug, dose), as.character(drug))
)
ggplot2::ggplot(
ex31_plot,
ggplot2::aes(x = PCV1, y = PCV2, color = treatment)
) +
ggplot2::geom_point(size = 2) +
ggplot2::geom_smooth(method = "lm", se = FALSE, linewidth = 0.8) +
ggplot2::labs(
x = "PCV at treatment",
y = "PCV one month later",
color = "Treatment",
title = "Relationship between baseline and follow-up PCV"
) +
ggplot2::theme_minimal()
