Informative missingness and MNAR sensitivity

Informative missingness and MNAR sensitivity. These functions form the eyeprocess 0.6.0.9000 measurement-intelligence programme and use dependency-free reference implementations with explicit evidence limits.

Usage

fit_process_observation_model(x, observed, predictors, random = c("person", "item"))
fit_joint_signal_missingness(outcome, observation, method = c("selection",
  "shared_parameter"), x = NULL, predictors = NULL)
process_pattern_mixture(x, delta = seq(-1, 1, 0.1), metric = NULL, estimand = mean)
sensitivity_mnar_process(x, estimand = mean, null = 0, ...)
plot_observation_probability(x, ...)
plot_missingness_by_time(x, ...)
plot_missingness_by_aoi(x, ...)
plot_mnar_tipping_point(x, ...)
plot_complete_case_sensitivity(x, ...)

Arguments

x

Input object or data structure appropriate for the selected analysis.

observed

Argument controlling `observed`; see the function usage and returned audit metadata.

predictors

Argument controlling `predictors`; see the function usage and returned audit metadata.

random

Argument controlling `random`; see the function usage and returned audit metadata.

outcome

Argument controlling `outcome`; see the function usage and returned audit metadata.

observation

Argument controlling `observation`; see the function usage and returned audit metadata.

method

Argument controlling `method`; see the function usage and returned audit metadata.

delta

Argument controlling `delta`; see the function usage and returned audit metadata.

metric

Argument controlling `metric`; see the function usage and returned audit metadata.

estimand

Argument controlling `estimand`; see the function usage and returned audit metadata.

null

Argument controlling `null`; see the function usage and returned audit metadata.

...

Additional arguments passed to the underlying method or plotting function.

Details

The APIs return auditable S3 objects. Plot wrappers call registered base-graphics methods. Experimental or approximate engines are labelled in object status fields and should be validated before confirmatory or operational use.

Value

An eyeprocess result object, data frame, model object, plot, or audit table as documented by the individual function.

See also

plot_diagnostics(), plot_evidence(), and plot_sensitivity().