Articles • NMAR

Step-by-step tutorials for using estimators in nmar package including both data.frame and survey design objects

Empirical Likelihood: Demonstrates the empirical likelihood estimator for Not Missing at Random outcomes implemented in the NMAR package, targeting the full-data mean under the Qin–Leung–Shao (2002) model. Includes data-frame and survey-design usage, auxiliary constraints, and bootstrap variance.
Exponential Tilting: Minsun Kim Riddles, Jae Kwang Kim, Jongho Im
A Propensity-score-adjustment Method for Nonignorable Nonresponse
https://doi.org/10.1093/jssam/smv047
Exponential Tilting (Nonparametric): Minsun Kim Riddles, Jae Kwang Kim, Jongho Im
A Propensity-score-adjustment Method for Nonignorable Nonresponse
Appendix 2
https://doi.org/10.1093/jssam/smv047

Developing a New NMAR Estimator: Guide for adding a new NMAR estimator to the NMAR package

Empirical Likelihood Theory for NMAR: Mathematical details and estimating-equation derivations for the empirical likelihood estimator for NMAR nonresponse implemented in the NMAR package, including the mapping from Qin–Leung–Shao (2002) paper to the code.
Exponential Tilting Theory
Nonparametric Exponential Tilting Theory