# A Pseudo-Likelihood Approach to Linear Regression With Partially Shuffled Data

@article{Slawski2019APA, title={A Pseudo-Likelihood Approach to Linear Regression With Partially Shuffled Data}, author={Martin Slawski and Guoqing Diao and Emanuel Ben-David}, journal={Journal of Computational and Graphical Statistics}, year={2019}, volume={30}, pages={991 - 1003} }

Abstract Recently, there has been significant interest in linear regression in the situation where predictors and responses are not observed in matching pairs corresponding to the same statistical unit as a consequence of separate data collection and uncertainty in data integration. Mismatched pairs can considerably impact the model fit and disrupt the estimation of regression parameters. In this article, we present a method to adjust for such mismatches under “partial shuffling” in which a…

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