Effect size in gctest

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Laurent
Laurent 2023 年 9 月 27 日
コメント済み: Scott 2024 年 11 月 23 日
Dear all,
I'm using gctest to test if there is any causation between three variables. The table is a 300 x 3, with 3 columns for each of the variables (let's call them A, B and C). Let's imagine that I find a significant granger-causality between A and B (A predicts B) and between A and C (A predicts C), how can I know the effect size of these two relationships? The test statistic is not useful here, among other reasons because I also need the sign of the causality (e.g., A predicts B, but this could be due to either A promotes or inhibits B).
Thanks a lot for your help!

回答 (1 件)

Avadhoot
Avadhoot 2023 年 10 月 3 日
Hi Laurent,
I understand that you have already performed the Granger causality test between variables A and B, as well as between variables A and C. To calculate the effect size for this causality, you can use the "meanEffectSize" function. This function calculates the mean-difference effect size between two samples. Please refer to the below documentation to know more about themeanEffectSize” function:
Here is a reference code for the same:
Effect = meanEffectSize(A, B);
Here's what this line does:
  1. Variables A and B should be numeric vectors representing the first and second samples, respectively.
  2. The "Effect" variable will contain a table with a row for each calculated effect size, and columns for the effect size value and confidence intervals.
For more information about Granger causality test, refer to the documentation below:
  • gctest function – Contains information about the Granger causality test function.
I hope it helps,
Regards,
Avadhoot.
  4 件のコメント
Laurent
Laurent 2023 年 10 月 4 日
Thanks for you time Avadhoot. However, if I compute meanEffectSize(A, B), I will get, as an effect size, the mean difference between A and B and not the effect size of A predicts B. To my understanding, meanEffectSize does not provide the effect size of causality, but I'd be happy to be provden wrong...
Scott
Scott 2024 年 11 月 23 日
Laurent wondering if you ever found an answer to this question? I'm trying to do the same thing.

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