Ideally, I would like to see reported the Odds-Ratio (OR) and the cell counts underlying the formation of the constituting probabilities.

Also, displaying the natural log transform of the OR would be informative as to quote a source:

The distribution of the log odds ratio is approximately normal...

and the source further notes a standard error could be computed based on an asymptotic approximation (relating to the square root of the sum of the respective reciprocals of the constituting cell counts).

This would allow the construction of confidence intervals (CIs) for the log(OR) (and also, median-centered CIs upon reversing the log transform), which would provide important information on precision (or lack there-of).

Further, if there are likely explanatory variables to account for variation across Log(OR), a generalized least-squares (as the individual logit points, per the standard error discussion above, have a known approximate relative error structure) model could be facilely explored to advance the information content.

Ideally, I would like to see reported the Odds-Ratio (OR) and the cell counts underlying the formation of the constituting probabilities.

Also, displaying the natural log transform of the OR would be informative as to quote a source:

The distribution of the log odds ratio is approximately normal...

and the source further notes, that a standard error estimate could be computed based on an asymptotic approximation (namely, the square root of the sum of the respective reciprocals of the constituting cell counts).

This would allow the construction of Normal distribution based confidence intervals (CIs) for the log(OR) (and also, median-centered CIs upon reversing the log transform), which would provide important information on precision (or lack there-of).

Further, if there are likely explanatory variables to account for variation across Log(OR), a generalized least-squares (as the individual logit points, per the standard error discussion above, have a known approximate relative error structure) model could be facilely explored to advance the information content.

Ideally, I would like to see reported the Odds-Ratio (OR) and the cell counts underlying the formation of the constituting probabilities.

Also, displaying the natural log transform of the OR would be informative as to quote a source, to quote:

The distribution of the log odds ratio is approximately normal...

and the source further notes a standard error could be computed based on an asymptotic approximation (relating to the square root of the sum of the respective reciprocals of the constituting cell counts).

This would allow the construction of confidence interval (CI) for the log(OR) (and also, a median centered CI upon reversing the log transform), which would provide important information on precision (or lack there-of).

Further, if there are likely explanatory variables to account for variation, a generalized least-squares (as the individual logit points, per the standard error discussion above, have a known approximate relative error structure) model could be facilely explored to advance the information content.

Ideally, I would like to see reported the Odds-Ratio (OR) and the cell counts underlying the formation of the constituting probabilities.

Also, displaying the natural log transform of the OR would be informative as to quote a source:

The distribution of the log odds ratio is approximately normal...

and the source further notes a standard error could be computed based on an asymptotic approximation (relating to the square root of the sum of the respective reciprocals of the constituting cell counts).

This would allow the construction of confidence intervals (CIs) for the log(OR) (and also, median-centered CIs upon reversing the log transform), which would provide important information on precision (or lack there-of).

Further, if there are likely explanatory variables to account for variation across Log(OR), a generalized least-squares (as the individual logit points, per the standard error discussion above, have a known approximate relative error structure) model could be facilely explored to advance the information content.