LogL.probit

Coeficient values the logliklihood should be drived at.

The value of the sensitivity parameter.

covariate matrix for missingness mechanism

covariate matrix for the outcome regression

indicator of wether y is missing or not

This function derives the Loglikelihood for <code><a rd-options="" href="/link/ui.probit?package=ui&version=0.1.1" data-mini-rdoc="ui::ui.probit">ui.probit</a></code>.

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

LogL.probit function

This function derives the Loglikelihood for <code><a rd-options='' href='ui.probit'>ui.probit</a></code>.

LogL.probit: Loglikelihood used by ui.probit

Description

Usage

Arguments