Cohen d greater than one


I am comparing two discrete variables (where the values can be one and zero only) with a third one using chi square test and Cohen d for the effect size. In my comparison, I found that my Cohen d was greater than one, with a significant p-value. I searched the web and found a vague post that said that this indicate that the difference between the means in this case is larger than the standard deviation. But how can I report such result? Is it valid? Does that mean that the effect is very strong or something else. Perhaps, chi square is not the right test? Sample data is given below and the results .

Thanks very much for your help.

this is how my data looks like.
var1 var2 var3
0 1 1
1 0 1
sample size: 827

I am trying to see how var3 is correlated with var1 and var2. The results of chi square between var3, var2 and var1 are:

cat p dof x2 cohenD
var1 0 1 65.586 -2.307
var2 0 1 191.834 -1.548


TS Contributor
You do not necessarily need to report effect size measures. You have only sample data, whereas effect
sizes are descriptions of populations. Your effect size measure will be larger or smaller than the true effect
size, due to sampling error.

Apart from that, Cohen's d is for the comparison of mean values of an interval scaled variable
between 2 groups. But seemingly, all of your variables are binary?

With kind regards

Thank you for your prompt reply. Yes all my variables are binary. So, I should shouldn't use Cohen d, I just need to report p? What about chi square, is it the right stat for my data?
Just rephrase my question appropriately, supposed I get more data and solve the balance of the data, would chi square be a valid test or should I still use logistic regression?
Well if you tell us more about the background context we can be of more help to you. One of the better effect estimates is to use risk differences, but you do not provide enough data for use to make particular recommendations given models will have assumptions.
I am doing a genetic study but tried to present my problem in a simple way. I have seven genes (my seven binary variables). I picked one gene and want to see how correlated are my six other genes with it, in 500 animals (my sample). I want to rank these genes by their strength of correlation. I used chi square and Cohen d. I used Cohen d to rank the genes (my assumption is that the bigger the cohen d the stronger the correlation, when p is valid of course).

I don't know if I can just rely on the chi square value to rank my variables. The bigger the chi2 the stronger the correlation. Also, I am not sure if logistic regression comes with something that can help me rank my variables like an effect size.

I collected my data from different sources, so Karabiner's idea that there is a sampling issue is reasonable.

Thanks for all for you help.
Is there correlation between the other genes? I wonder if naïve Bayes may work with your data?

A simple approach may be to just calculate the probability of the genes with the outcome and provide 99% confidence intervals.

Bigger picture you could use logistic regression, but you would want to think about interaction terms - whether they are necessary and how many combination there can be.
I think there are correlations between the other genes. After the issue I had with this first case, I stopped my work ...
Thanks for your help.