population moments?

[mcfrank]

Hi @mayamathur, another one for you:

we were discussing this figure:

(I've changed the X axis to be "effect size")

You wrote: "Here too, not sure if "effect" is the right term since this is just a population moment." I was seeing these pictures as distributions of effect sizes within subgroups in the population. The revised version reads:

The convenience sample doesn't cause problems if the size of your effect is homogeneous in the population -- as with the case of smoodling or Stroop. The trouble comes when you have an effect that is heterogeneous. Because one group is over-represented, you get systematic bias in the sample mean relative to the population mean.

Does this seem OK with you?

[mayamathur]

Yes, I think that makes sense! I guess it's a little complicated that there is still residual effect heterogeneity even conditional on subgroup, but I don't feel strongly about changing it further.

On Thu, Sep 14, 2023 at 7:28 PM Michael Frank @.***> wrote:

Hi @mayamathur https://github.com/mayamathur, another one for you:

we were discussing this figure: [image: heterogeneity] https://user-images.githubusercontent.com/1158807/268132420-2cb80a4a-e092-4180-9d10-4fa4b6297184.png

(I've changed the X axis to be "effect size")

You wrote: "Here too, not sure if "effect" is the right term since this is just a population moment." I was seeing these pictures as distributions of effect sizes within subgroups in the population. The revised version reads:

The convenience sample doesn't cause problems if the size of your effect is homogeneous in the population -- as with the case of smoodling or Stroop. The trouble comes when you have an effect that is heterogeneous. Because one group is over-represented, you get systematic bias in the sample mean relative to the population mean.

Does this seem OK with you?

— Reply to this email directly, view it on GitHub https://github.com/langcog/experimentology/issues/190, or unsubscribe https://github.com/notifications/unsubscribe-auth/ACEE6HTGYZUZLI2WSUYEXQLX2OHIJANCNFSM6AAAAAA4Y7UQRU . You are receiving this because you were mentioned.Message ID: @.***>

--

Maya Mathur Assistant Professor Quantitative Sciences Unit https://med.stanford.edu/qsu.html, Biomedical Informatics Research Division Associate Director, Center for Open and Reproducible Science https://datascience.stanford.edu/cores Stanford University Website http://www.mayamathur.com

https://med.stanford.edu/profiles/maya-mathur

[mcfrank]

great, thanks!