A Finite Population Likelihood Ratio Test of the Sharp Null Hypothesis for Compliers

Wen Wei Loh, Thomas Richardson
Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence, PMLR R13:269-278, 2015.

Abstract

In a randomized experiment with noncompliance, scientific interest is often in testing whether the treatment exposure X has an effect on the final outcome Y. We propose a finite-population significance test of the sharp null hypothesis that X has no effect on Y, within the principal stratum of compliers, using a generalized likelihood ratio test. We present a new algorithm that solves the corresponding integer programs.

Cite this Paper

BibTeX
@InProceedings{pmlr-vR13-loh15a, title = {A Finite Population Likelihood Ratio Test of the Sharp Null Hypothesis for Compliers}, author = {Loh, Wen Wei and Richardson, Thomas}, booktitle = {Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence}, pages = {269--278}, year = {2015}, editor = {Meila, Marina and Heskes, Tom}, volume = {R13}, series = {Proceedings of Machine Learning Research}, month = {12--16 Jul}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/r13/main/assets/loh15a/loh15a.pdf}, url = {https://proceedings.mlr.press/r13/loh15a.html}, abstract = {In a randomized experiment with noncompliance, scientific interest is often in testing whether the treatment exposure X has an effect on the final outcome Y. We propose a finite-population significance test of the sharp null hypothesis that X has no effect on Y, within the principal stratum of compliers, using a generalized likelihood ratio test. We present a new algorithm that solves the corresponding integer programs.}, note = {Reissued by PMLR on 04 October 2026.} }
Endnote
%0 Conference Paper %T A Finite Population Likelihood Ratio Test of the Sharp Null Hypothesis for Compliers %A Wen Wei Loh %A Thomas Richardson %B Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence %C Proceedings of Machine Learning Research %D 2015 %E Marina Meila %E Tom Heskes %F pmlr-vR13-loh15a %I PMLR %P 269--278 %U https://proceedings.mlr.press/r13/loh15a.html %V R13 %X In a randomized experiment with noncompliance, scientific interest is often in testing whether the treatment exposure X has an effect on the final outcome Y. We propose a finite-population significance test of the sharp null hypothesis that X has no effect on Y, within the principal stratum of compliers, using a generalized likelihood ratio test. We present a new algorithm that solves the corresponding integer programs. %Z Reissued by PMLR on 04 October 2026.
APA
Loh, W.W. & Richardson, T.. (2015). A Finite Population Likelihood Ratio Test of the Sharp Null Hypothesis for Compliers. Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence, in Proceedings of Machine Learning Research R13:269-278 Available from https://proceedings.mlr.press/r13/loh15a.html. Reissued by PMLR on 04 October 2026.

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