Creates a visualization of the additive sender (row) and receiver (column) random effects from an AME or LAME model. Automatically detects whether effects are static or dynamic and provides appropriate visualization options.
Arguments
- fit
An object of class "ame" or "lame" from fitting an AME model
- effect
Character string specifying which effect to plot: "sender" (default) or "receiver"
- sorted
Logical; if TRUE (default), actors are sorted by effect magnitude
- labels
Logical; if TRUE, actor labels are shown on x-axis (default TRUE for n <= 50 actors)
- title
Optional title for the plot
- time_point
For dynamic effects, which time point to plot (default: last). Can be numeric index, "all" for faceted plot, or "average" for time-averaged
- plot_type
For dynamic effects: "snapshot" (single time), "trajectory" (evolution over time), "faceted" (grid of time points), or "ribbon" (confidence bands over time). For static effects, this parameter is ignored.
- show_actors
Character vector of specific actors to highlight (for dynamic trajectory/ribbon plots)
Details
The additive effects in AME models represent:
- Sender effects (a)
Actor-specific tendencies to form outgoing ties. Positive values indicate actors who send more ties than expected; negative values indicate actors who send fewer ties.
- Receiver effects (b)
Actor-specific tendencies to receive incoming ties. Positive values indicate actors who receive more ties than expected; negative values indicate actors who receive fewer ties.
For static effects, the plot displays these effects as a dot plot with vertical lines extending from zero to each effect estimate.
For dynamic effects (when fit contains a_dynamic/b_dynamic), additional options are available to visualize how effects evolve over time.
Examples
if (FALSE) { # \dontrun{
# Fit an AME model
fit <- ame(Y, X)
# Visualize sender effects
ab_plot(fit, effect = "sender")
# Visualize receiver effects without sorting
ab_plot(fit, effect = "receiver", sorted = FALSE)
# Customize the plot
library(ggplot2)
ab_plot(fit) + theme_minimal() + ggtitle("Network Sender Effects")
} # }