getCI: Sensitivity Analysis for Binary Missing Data

In salbm: Sensitivity Analysis for Binary Missing Data

Description

Given an object returned by salbmCombine the getCI function extracts estimates and confidence intervals.

Usage

getCI( Res, ci=c("lb4","ub4") )

Arguments

Res	an object returned by salbmM, salbm with confidence intervals
ci	indicates which confidence interval to return. See the help for salbmCombine for the list of confidence interval types.

Details

Looks for ECI and SCI in the input object. ECI contains confidence bands for estimates of E[ Yt | alpha ] and their differences. SCI contains confidence bands for estimates of the cumulative sum E[ Y1+Y2+...+YK | alpha ] and their differences.

Value

returns a list with 1. K the value of the last timepoing 2. alphas the vector of sensitivity parameters 3. ER1 an n by 4 matrix where n is the length of the alphas vector. ER1 contains expected values of Y at time K for the first treatment group trt1. The columns are alpha, E[Y_K| alpha], lb, ub where lb and ub are the lower bound and upper bound of the confidence interval chosen. 4. ER2 as ER1 but for the second treatment arm trt2. 5. ERD the difference in estimates trt2 - trt1. 6. SR1 cumulative sum estimates for trt 1 7. SR2 cumulative sum estimates for trt 2 8. SRD differences in cumulative sum estimates trt 2 - trt 1.

Examples

  # select confidence interval type 
  Res  <-  getCI( R, ci=c("lb2","ub2"))
  ER1  <-  Res$ER1
  plot( x = ER1[,1], y = ER1[, 2] )

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