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DOI

https://doi.org/10.7275/yke1-k937

Abstract

Although they test somewhat different hypotheses, analysis of gain scores (or its repeated-measures analog) and analysis of covariance are both common methods that researchers use for pre-post data. The results of the two approaches yield non-comparable outcomes, but since the same generic data are used, it is possible to transform the test statistic of one into that of the other. We derive a formula that can be used to accomplish a conversion between the two and give an example. Such a result could be helpful to meta-analysts, where the outcomes in different research reports may be of either of the two types, yet need to be synthesized. Suggestions for additional research that can improve the usefulness of the formula are offered. Accessed 30,293 times on https://pareonline.net from March 20, 2009 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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