ML.probit

out.formula

Formula for regression model for the missingness mechanism.

mis.formula

Data frame containing the variables in the formulas

data

Vector containing the values of rho for which we want to fit the likelihood.

If TRUE prints out process time for each maximazation of the likelihood.

progress

Maximazation method to be passed through <code>maxLik</code>

method

This is a support function 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

ML.probit function

This is a support function for <code><a rd-options='' href='ui.probit'>ui.probit</a></code>

ML.probit: Fit maximum likelihood for fixed values of rho

Description

Usage

Arguments