plot_lmmModel {SynergyLMM} | R Documentation |
Plotting of tumor growth data from a fitted model
Description
Vizualization of tumor growth data and linear mixed model fitted regression line for the fixed effects. This functions returns a ggplot2 plot, allowing for further personalization.
Usage
plot_lmmModel(
model,
trt_control = "Control",
drug_a = "Drug_A",
drug_b = "Drug_B",
drug_c = NA,
combination = "Combination"
)
Arguments
model |
An object of class "lme" representing the linear mixed-effects model fitted by |
trt_control |
String indicating the name assigned to the 'Control' group. |
drug_a |
String indicating the name assigned to the 'Drug A' group. |
drug_b |
String indicating the name assigned to the 'Drug B' group. |
drug_c |
String indicating the name assigned to the 'Drug C' group (if present). |
combination |
String indicating the name assigned to the Combination ('Drug A' + 'Drug B', or 'Drug A' + 'Drug B' + 'Drug C') group. |
Value
A ggplot2 plot (see ggplot2::ggplot()
for more details) showing the tumor growth data represented as log(relative tumor volume) versus time since treatment initiation.
The regression lines corresponding to the fixed effects for each treatment group are also plotted.
Examples
data(grwth_data)
# Fit the model
lmm <- lmmModel(
data = grwth_data,
sample_id = "subject",
time = "Time",
treatment = "Treatment",
tumor_vol = "TumorVolume",
trt_control = "Control",
drug_a = "DrugA",
drug_b = "DrugB",
combination = "Combination",
show_plot = FALSE
)
# Default plot
plot_lmmModel(lmm,
trt_control = "Control",
drug_a = "DrugA",
drug_b = "DrugB",
combination = "Combination"
)
# Adding ggplot2 elements
plot_lmmModel(lmm,
trt_control = "Control",
drug_a = "DrugA",
drug_b = "DrugB",
combination = "Combination"
) + ggplot2::labs(title = "Example Plot") + ggplot2::theme(legend.position = "top")