sandImpACE

Coefficients from non-treated regression.

BetaOLSy0

Coefficients from treated regression.

BetaOLSy1

NaivEst

Number of covariates outcome regression.

This is a support function for <code><a rd-options="" href="/link/ui.causal?package=ui&version=0.1.1" data-mini-rdoc="ui::ui.causal">ui.causal</a></code> and calculates standard error of Average causal effect for the regression imputation estimator.

Implements functions to derive uncertainty intervals for (i) regression (linear and probit) parameters when outcome is missing not at random (non-ignorable missingness) introduced in Genbaeck, M., Stanghellini, E., de Luna, X. (2015) <doi:10.1007/s00362-014-0610-x> and Genbaeck, M., Ng, N., Stanghellini, E., de Luna, X. (2018) <doi:10.1007/s10433-017-0448-x>; and (ii) double robust and outcome regression estimators of average causal effects (on the treated) with possibly unobserved confounding introduced in Genbaeck, M., de Luna, X. (2018) <doi:10.1111/biom.13001>.

Minna Genbaeck

Uncertainty Intervals and Sensitivity Analysis for Missing Data

sandImpACE function

This is a support function for <code><a rd-options='' href='ui.causal'>ui.causal</a></code> and calculates standard error of Average causal effect for the regression imputation estimator.

sandImpACE: Calculates standard error of Average causal effect

Description

Usage

Arguments