residual_plot: Function to generate conditional regression equation plots...

In rblimp: Integration of 'Blimp' Software into R

Function to generate conditional regression equation plots (i.e., simple effects) with rblimp and SIMPLE command

Description

Generates a conditional effect plots based on the posterior summaries from the output of rblimp.

Usage

residual_plot(
  model,
  variable,
  nsigma = 1,
  point_col = "black",
  horz_line = "black",
  col1 = "#0571b0",
  col2 = "#ca0020",
  linewidth = 1.1,
  ...
)

Arguments

model	an blimp_obj. The object must have a SIMPLE command output saved.
variable	the name of the outcome for which to create a plot
nsigma	the number of standard deviations to produce credible bounds
point_col	the color of the points in the plot
horz_line	the color of the horiztonal zero line
col1	the color of the loess mean line
col2	the color of the loess credible bound lines
linewidth	the linewidth value for the loess lines and its bounds.
...	arguments passed to loess call used to loess lines.

Details

All colors are passed into ggplot2. See ggplot2::aes_colour_fill_alpha for details on changing colors.

Value

a ggplot2::ggplot plot

Examples

# Generate Data
mydata <- rblimp_sim(
    c(
        'x ~ normal(0, 1)',
        'm ~ normal(0, 1)',
        'y ~ normal(10 + 0.5*x + m + 0.2*x*m, 1)'
    ),
    n = 100,
    seed = 981273
)

# Run Rblimp
m1 <- rblimp(
    'y ~ x m',
    mydata,
    nimps = 10,
    seed = 10972,
    burn = 1000,
    iter = 1000
)

# Generate Plot
residual_plot(m1, 'y') + ggplot2::theme_minimal()

rblimp documentation built on May 18, 2026, 9:07 a.m.