I've come across a series of association studies that report odds and asymmetric confidence intervals. The standard meta-analytic techniques I've used assume symmetrical confidence intervals to calculate the standard error. I'm not sure if there are standard practices for this and here my naive thoughts:

1. Use the smaller CI and calculate the SE from it. This would assume it was calculated using a consistency standard error and that the other CI was calculated using an agreement standard error.

2. Calculate the log(OR) and it's SE assuming that both boundaries were calculated using a consistency standard error (which we know it's true).

3. Use some other approach (haven't found any in the literature) and/ or software functions.

Data looks like this:

1.03 1.00 1.06

1.012 1.011 1.014

1.35 1.16 1.59

1.89 1.1 3.26

I've come across a series of association studies that report odds and asymmetric confidence intervals. The standard meta-analytic techniques I've used assume symmetrical confidence intervals to calculate the standard error. I'm not sure if there are standard practices for this and here my naive thoughts:

1. Use the smaller CI and calculate the SE from it. This would assume it was calculated using a consistency standard error and that the other CI was calculated using an agreement standard error.

2. Calculate the log(OR) and its SE assuming that both boundaries were calculated using a consistency standard error (which we know it's true).

3. Use some other approach (haven't found any in the literature) and/or software functions.

Data looks like this:

1.03 1.00 1.06
1.012 1.011 1.014
1.35 1.16 1.59
1.89 1.1 3.26