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Tagged with cohens-d statistical-significance
9 questions
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Effect size and statistical significance correspondence
While I understand that it is possible to have a small effect size with statistical significance and a large effect size without statistical significance, is it ever possible to find this across two ...
- 11
6
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2
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11k
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When to use Cohen's d and when t-test?
When do I use Cohen's and when do I t-test? Probably in addition: What is the (conceptual) difference between them? Both tests are meant to study the difference between two distributions.
I just ...
- 3,493
2
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1
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269
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How can Cohen's d < 1.96 ever be statistically significant?
I am having trouble understanding the statistical significance of Cohen's d.
My reasoning goes like this:
To conclude that experimental group differs from control group significantly (p < 0.05), ...
- 21
1
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1
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473
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Is the Cohen's D a suitable test for my dataset?
I have two variables (A and B). A has 3,000 samples; B ...
- 307
3
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1k
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Statistical comparison of 2 dependent cohen's ds
How would I statistically test the significane of the difference between two Cohen's d derived from different tests within the same sample?
Specifically, in my neuroimaging data metabolism in brain ...
- 31
4
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4
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673
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Specific interpretation of non-significant test considering power and effect size
Assuming a test where p > alpha and n is large enough for power > 95% at effect size d, what is the exact interpretation of the test regarding the relationship between the observed data, the real ...
- 1,844
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62
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Concordance test and corresponding plot
I have a list of genes identified using algorithm_A, then using algorithm_B and finally using algorithm_C; then a second list of genes identified using algorithm_A, then using algorithm_B and then ...
- 213
5
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808
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How to assess whether two treatments are significantly different using Cohen's d (effect size)?
Cohen's d is a measure of effect size calculated as:
$d = (x_1-x_2) / \sigma_{\text{pooled}}$
where $x_1$ is the mean of one group, $x_2$ is the mean of a second group, and $\sigma_{\text{pooled}}$ ...
- 101
7
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3
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18k
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Effect size and statistical significance
Using Cohen's $d$, I am getting small and medium effect sizes for results that are statistically non-significant ($p>.05$). Does this make sense?
