A comparative review of methods for comparing means using partially paired data

@article{Guo2017ACR,
  title={A comparative review of methods for comparing means using partially paired data},
  author={Beibei Guo and Ying Yuan},
  journal={Statistical Methods in Medical Research},
  year={2017},
  volume={26},
  pages={1323 - 1340}
}
In medical experiments with the objective of testing the equality of two means, data are often partially paired by design or because of missing data. The partially paired data represent a combination of paired and unpaired observations. In this article, we review and compare nine methods for analyzing partially paired data, including the two-sample t-test, paired t-test, corrected z-test, weighted t-test, pooled t-test, optimal pooled t-test, multiple imputation method, mixed model approach… 

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