I wanted to know if standard error of log odds ratio and standard error of SMD is the same in meta analysis.
Thank you.
Dear Paul,
"There are statistical approaches available which will re-express odds ratios as standardized mean differences (and vice versa), allowing dichotomous and continuous data to be pooled together. Based on an assumption that the underlying continuous measurements in each intervention group follow a logistic distribution (which is a symmetrical distribution similar in shape to the normal distribution but with more data in the distributional tails), and that the variability of the outcomes is the same in both treated and control participants, the odds ratios can be re-expressed as a standardized mean difference according to the following simple formula (Chinn 2000):
.The standard error of the log odds ratio can be converted to the standard error of a standardized mean difference by multiplying by the same constant (√3/ π = 0.5513). Alternatively standardized mean differences can be re-expressed as log odds ratios by multiplying by π/√3 = 1.814. Once standardized mean differences (or log odds ratios) and their standard errors have been computed for all studies in the meta-analysis, they can be combined using the generic inverse-variance method in RevMan. Standard errors can be computed for all studies by entering the data in RevMan as dichotomous and continuous outcome type data, as appropriate, and converting the confidence intervals for the resulting log odds ratios and standardized mean differences into standard errors"
http://handbook.cochrane.org/chapter_9/9_4_6_combining_dichotomous_and_continuous_outcomes.htm
No. They are different. SMD (its SE) helps you to standardize different outcome measurands into identical/uniform scale so you can later combine and run a meta-analysis. SMDs, ORs..are among different methods used to describe effect sizes.
You can though make them compatible by the above given advise!
LogSE is the standard error of the log odds ratio. This is used to estimate variance of effect size estimates in case of binary outcomes .
SMD is the stardardized mean difference is an effect size measure in case of continuos outcomes.
Once again:
The standard error of the log odds ratio can be converted to the standard error of a standardized mean difference by multiplying by the same constant (√3/ π = 0.5513). Alternatively standardized mean differences can be re-expressed as log odds ratios by multiplying by π/√3 = 1.814.
After that they are the "same" or compatible in a meta analysis
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