Plot fitted values of M and Y from multilevel mediation model

Plot population-level fitted values and X values, for M and Y.

mlm_spaghetti_plot(
  mod = NULL,
  d = NULL,
  id = "id",
  x = "x",
  m = "m",
  y = "y",
  level = 0.95,
  n = 12,
  binary_y = FALSE,
  mx = "fitted",
  fixed = TRUE,
  random = TRUE,
  h_jitter = 0,
  v_jitter = 0,
  bar_width = 0.2,
  bar_size = 0.75,
  n_samples = NA
)

Arguments

mod: A multilevel mediation model estimated with mlm().
d: A data.frame or a data_frame used in fitting model.
id: Name of id variable (identifying subjects) in data (d).
x: Name of X variable in data.
m: Name of M variable in data.
y: Name of Y variable in data.
level: X level for Credible Intervals. (Defaults to .95.)
n: Number of points along X to evaluate fitted values on. See details.
binary_y: Set to TRUE if the outcome variable (Y) is 0/1.
mx: Should the X axis of the M-Y figure be "fitted" values, or "data" values. Defaults to "fitted".
fixed: Should the population-level ("fixed") fitted values be shown?
random: Should the subject-level ("random") fitted values be shown?
h_jitter: Horizontal jitter of points. Defaults to 0.
v_jitter: Vertical jitter of points. Defaults to 0.
bar_width: Width of the error bars. Defaults to 0.2.
bar_size: Thickness of the error bars. Defaults to 0.75.
n_samples: Number of MCMC samples to use in calculating fitted values. See details.

Value

A list of two ggplot2 objects.

Details

If n = 2, the fitted values will be represented as points with X line with a Confidence Ribbon instead. If a very large model is fitted with a large number of MCMC iterations, the function might take a long time to run. In these cases, users can set n_samples to a smaller value (e.g. 1000), in which case the fitted values (and the CIs) will be based on a random subset of n_samples MCMC samples. The default value is NA, meaning that all MCMC samples are used.

Author

Matti Vuorre mv2521@columbia.edu