Effect size in regression

css

Member
Hi everyone,
I am reading an article at which authors used an effect size that it's totally new to me and I do not know how to interpret it. I would appreciate if anyone could explain its meaning or provide any reference about its interpretation. Below, I paste some sentences from the original article at which the authors' explain how data were analyzed, highlighting in bold the effect size description.

We used linear regression model (...) Analytically, we regressed one of the outcomes on the indicator for opposite sex (β) and the set of control variables (λ). C In the main regressions, the estimate on opposite sex (β) compared the mean outcomes between females exposed to a male and females exposed to a female. Figs 1 and 2 plot effect sizes, that is, the point estimate divided by mean of an outcome in the estimation sample

My questions are: 1) why beta (which I assume is the standardized regression weight) was divided by the mean of the estimation sample?; 2) Would not have been better just to use the b (unstandardized) weights as a measure of effect size (or to divide b by the SD of the sample to have an approximation to Cohen's d)?

hlsmith

Not a robit
I could not tell from that snippet, but it does seem as though they are trying to get at a standardized coefficient, which seem popular in the social sciences since you can try to rank the coefficients by it. Not well versed in the methods.

css

Member
Hi hlsmith,
Unfortunately, the methods section is very short and table/ figure legends do not provide further details. Let's see if anyone else has seen this procedure before and can provide further details. In any case, your answer is very much appreciated

hlsmith

Not a robit
You can also post a link to the paper. That may help others as well.

noetsi

Fortran must die
I think they are trying to standardize the slopes as well. Generally this is doubtful with dummy variables like gender which can take on only two levels.

Hi Noetsi,