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I have used paired t-test to validate the hypothesis using my data from R. Is there any research article related to t-test in R?

If there is any article related to t-test in R, please let me know.

C8H10N4O2
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Exchhattu
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    I think this is more related to [http://stats.stackexchange.com/](http://stats.stackexchange.com/) – zx8754 Sep 18 '13 at 07:55

2 Answers2

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A good place to look in general for citations is the documentation of the function. In this case however, a paired t-test is so basic that you can simply refer to an introductory statistics book that describes the test.

Paul Hiemstra
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  • Thanks, I already thought that too. However, I have used it from R. It is better to cite form R if available. – Exchhattu Sep 18 '13 at 08:04
  • The t-test in R is simply the standard implementation of the t-test, so there is no specific need to cite R. I sometimes have added to a paper of mine that I did the analyses in R. But this was more of a remark in the Acknowledgements section. – Paul Hiemstra Sep 18 '13 at 08:07
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    I always state (with the reference `citation()` asks for) in my Methods section that a specific R version was used. – Roland Sep 18 '13 at 08:47
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I agree with Paul that for the paired t-test with a pooled SD (mean of pretest SD and posttest SD), you don't necessarily need a citation. Nevertheless, there are more sophisticated methods like raw score standardization or change score standardization, e.g. implemented by the metafor package.

So for what it's worth, here are some related references.

Morris, Scott B. 2008. “Estimating Effect Sizes From Pretest-Posttest-Control Group Designs.” Organizational Research Methods 11 (2): 364–86. Davis, John M. 1993. “Experiments Involving Paired Comparisons” 18 (3): 271–79.

Fritz, Catherine O., Peter E. Morris, and Jennifer J. Richler. 2012. “Effect Size Estimates: Current Use, Calculations, and Interpretation.” Journal of Experimental Psychology: General 141 (1): 2–18. https://doi.org/10.1037/a0024338.

Lakens, Daniël. 2013. “Calculating and Reporting Effect Sizes to Facilitate Cumulative Science: A Practical Primer for t-Tests and ANOVAs.” Frontiers in Psychology 4 (NOV): 1–12. https://doi.org/10.3389/fpsyg.2013.00863.

Morris, Scott B., and Richard P. DeShon. 2002. “Combining Effect Size Estimates in Meta-Analysis with Repeated Measures and Independent-Groups Designs.” Psychological Methods 7 (1): 105–25. https://doi.org/10.1037/1082-989X.7.1.105.

O’Brien, Fearghal, and Denis Cousineau. 2015. “Representing Error Bars in Within-Subject Designs in Typical Software Packages.” The Quantitative Methods for Psychology 11 (2): 126–126. https://doi.org/10.20982/tqmp.11.2.p126.

Cousineau, Denis. 2005. “Confidence Intervals in Within-Subject Designs: A Simpler Solution to Loftus and Masson’s Method.” Tutorials in Quantitative Methods for Psychology 1 (1): 42–45.

Agile Bean
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