PrepInferenceAssumption: Sensitivity Analysis for Binary Missing Data

In salbm: Sensitivity Analysis for Binary Missing Data

Description

Given an object returned from salbmCombine this function prepares results for presentation in a table.

Usage

PrepInferenceAssumption(M, CItp=2, qt = c(0.025, 0.975), SampCIType=1, carm=2)

Arguments

M	is an object returned by the salbm function salbmCombine. It should contain confidence bands ECI and SCI and means and standard deviations from bootstraps (Main1wts, Main2wts, Samp1wts and Samp2wts).
CItp	a number ranging from 1 to 4, indicating which confidence interval to use.
qt	two values passed to quantile in producing confidence intervals.
SampCIType	type of CI for samples
carm	comparison arm

Details

PrepInferenceAssumption is used in conjunction with influenceAssumption to produce a summary of an salmb results object,

It produces summeries for each arm of the study and the difference in estimates between arms under various assumptions:

MCAR when the mean value is substituted for missing at each timepoint

missing=0 when 0 is substituted for missing at each timepoint

missing=1 when 1 is substituted for missing at each timepoint

benchmark results returned from salbm or salbmM

Value

a matrix which inferenceAssumption can display.

See Also

salbm, salbmM, influenceAssumption

Examples

  # M is an object returned from salbm's salbmCombine function

  prep <- PrepInferenceAssumption( M )
  inferenceAssumption(prep)

salbm documentation built on May 25, 2021, 9:07 a.m.