Chi-Square test of Independce in R - ALL IN ONE (Calculation, Interpretation, Reporting)

// Chi-Square test of Independce in R - ALL IN ONE (Calculation, Interpretation, Reporting) //

This video will help you in conducting a Chi-Square test of independence in R, including the calculation of post-hoc-tests, the effect size as well as interpreting and reporting its results.

Please don't forget that an a priori sample size calculation is usually required.

Calculating the required sample size:
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🎥    • Two sample t-test - calculate require...  


The video consists of the following five parts:
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1) Calculation of the Chi-Square test of independence in R using the CrossTable()-function. A cross table is also interpreted. The Chi-Square test will be substituted by the Fisher test when expected cell frequencies of the cross table are smaller than 5. The Fisher test calculates an exact p-value.

2) Conducting post-hoc-tests to see which cell of the contingency table shows deviations of expected and observed frequencies.

3) Interpretation of the results, especially the post-hoc-tests.

4) Calculation of the effect size for the Chi-Square test of Independence, Cohen's w.

5) Reporting of the results. Be aware that research field-specific standards may apply. The reporting shown is usually sufficient.


General information on the Chi-Square-test of Independence
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The Chi-Square test of independence is used for testing two categorical or ordinal variable (with a limited number of characteristics) for independence.

Within it, a contingency table is used to see the observed frequencies, meaning the actual combinations of characteristics of the two variables. The expected counts are calculated under the assumption of independence of the two variables. Finally, the difference between expected and observed counts is calculated.


📚 Sources:
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Lantz, B. (2013). The large sample size fallacy. Scandinavian journal of caring sciences, 27(2), 487-492.


⏰ Timestamps:
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0:00 Introduction
0:14 Example
0:25 Creating contingency table
0:50 Adding expected counts
1:54 Interpreting Chi-Square Independence test
2:25 Interpreting the Fisher's exact test
2:46 Calculate post-hoc-tests
4:09 Interpreting post-hoc-tests
5:12 Calculating the effect size Cohen's w
6:14 Reporting the results


If you have any questions or suggestions regarding the Chi-Square test of Independce, please use the comment function. Thumbs up or down to decide if you found the video helpful. #statisticampc

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