# 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 approachâ€¦Â Expand

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#### References

SHOWING 1-10 OF 31 REFERENCES

A method for comparing two normal means using combined samples of correlated and uncorrelated data.

- Mathematics, Medicine
- Statistics in medicine
- 2003

Using the general linear mixed model to analyse unbalanced repeated measures and longitudinal data.

- Mathematics, Medicine
- Statistics in medicine
- 1997