The data are measurements of treatment vs control. Sample size (n) is 3 and the data include both positive and negative values and zeros.

To use logRR (log response ratio), a transformation is required (adding the absolute minimal negative value,  and assigning an arbitrarily small value instead of zero). I understand that these transformations are not recommended. Alternatively, Hedges' g can be used without any transformations.

The problem arises from the high variance (due to low sample size) in some cases, where the Hedges' g (that include SD in the denominator) is much lower than logRR, although its error estimate (for example, confidence interval) is larger. Then, a different interpretation can take place - small effect with low uncertainty using Hedges' g, and large effect with high uncertainty using logRR.

Attached is an example of the two estimators for the same data.

What would be the best practice?

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