Methods for modular wsMed objects

Usage

# S3 method for class 'wsMed'
print(
  x,
  digits = 3,
  detail = c("effects", "full", "overview", "legacy"),
  type = "all",
  at = NULL,
  standardized = NULL,
  method = NULL,
  level = NULL,
  scale = NULL,
  ...
)

# S3 method for class 'wsmed_model'
print(x, ...)

# S3 method for class 'wsmed_fit'
print(x, digits = 3, ...)

# S3 method for class 'wsmed_inference'
print(x, ...)

# S3 method for class 'wsmed_fit'
summary(object, ...)

# S3 method for class 'summary_wsmed_fit'
print(x, digits = 3, ...)

# S3 method for class 'wsmed_inference'
summary(
  object,
  type = "all",
  at = NULL,
  scale = NULL,
  standardized = NULL,
  ...
)

# S3 method for class 'wsMed'
summary(
  object,
  type = "all",
  at = NULL,
  scale = NULL,
  method = NULL,
  standardized = NULL,
  ...
)

# S3 method for class 'wsmed_fit'
coef(object, ...)

# S3 method for class 'wsmed_fit'
vcov(object, ...)

# S3 method for class 'wsmed_fit'
nobs(object, ...)

# S3 method for class 'wsmed_inference'
coef(object, ...)

# S3 method for class 'wsmed_inference'
vcov(object, ...)

# S3 method for class 'wsmed_inference'
nobs(object, ...)

# S3 method for class 'wsMed'
coef(object, ...)

# S3 method for class 'wsMed'
vcov(object, ...)

# S3 method for class 'wsMed'
nobs(object, ...)

# S3 method for class 'wsmed_fit'
confint(object, parm, level = NULL, ...)

# S3 method for class 'wsmed_inference'
confint(object, parm, level = NULL, standardized = NULL, scale = NULL, ...)

# S3 method for class 'wsMed'
confint(
  object,
  parm,
  level = NULL,
  method = NULL,
  standardized = NULL,
  scale = NULL,
  ...
)

# S3 method for class 'wsmed_results'
print(x, digits = 3, ...)

# S3 method for class 'wsmed_results'
summary(object, level = NULL, ...)

# S3 method for class 'wsmed_results'
as.data.frame(x, row.names = NULL, optional = FALSE, ...)

# S3 method for class 'wsmed_results'
coef(object, ...)

# S3 method for class 'wsmed_results'
vcov(object, ...)

# S3 method for class 'wsmed_results'
confint(object, parm, level = NULL, ...)

# S3 method for class 'summary_wsmed'
print(x, digits = 3, ...)

# S3 method for class 'summary_wsmed'
summary(object, level = NULL, ...)

Arguments

x, object: A wsMed or modular workflow object.
digits: Number of displayed digits. Stored estimates are not rounded.
detail: effects (default) for core effects, full for effects and path coefficients, overview for fit status, or legacy for original stored tables.
type, at, scale, method: Passed to wsmed_effects(). Summaries default to all core effects. Select method when both inference engines are stored.
standardized: NULL inherits the saved analysis setting; TRUE or FALSE overrides it without fitting or sampling. Applies with or without moderation.
level: Confidence level. NULL uses the level saved in the selected inference or results object.
...: Additional arguments, passed to effect extraction by summary and confint methods. See wsmed_plots for plotting arguments.
parm: Names or positions of parameters/effects to include in intervals.
row.names, optional: Standard data-frame conversion arguments.

Value

print methods return their input invisibly. summary returns a summary_wsmed (also a wsmed_results) for inference/one-call objects, or a summary_wsmed_fit for fits. Structured summaries contain effects and coefficients data frames, info, diagnostics and selected joint effect draws. as.data.frame, coef, confint, vcov and plot on the summary concern the selected effects; coefficients contains conditional path slopes (not all primitive parameters). Use type = 'parameters' for primitive parameters. Summary display uses printCoefmat; tables retain full precision. coef returns a named numeric vector. vcov returns the fit covariance (Rubin-pooled for MI), or the empirical covariance of stored draws for inference/results. confint recomputes percentile limits from stored draws without sampling. Its default level is the saved level, including when called on an inference or one-call object; use an explicit level to override it. On those two classes confint concerns native primitive parameters, matching coef and vcov regardless of the reporting preference (explicit scale overrides are accepted). Fit-only summaries also describe native parameters. Extract effects first to obtain indirect/conditional-effect intervals. nobs returns the sample size for each fitted dataset. as.data.frame returns a full-precision results table. plot returns a ggplot.

Methods for modular wsMed objects

Usage

Arguments

Value

See also