Could you please apply your logic step by step to the three coefficients?
On Sun, Sep 26, 2021 at 1:39 AM Juho Kristian Ruohonen
<juho.kristian.ruohonen at gmail.com> wrote:
In my view, your logic is slightly oversimplified (i.e. incorrect).
Regression models do not estimate coefficients by holding predictors
constant exclusively at the reference category. They do something more
general, namely estimate coefficients by holding predictors constant at any
value at which variation is observed in the values of the other predictors.
su 26. syysk. 2021 klo 9.03 Simon Harmel (sim.harmel at gmail.com)
Dear Juho and other List Members,
My problem is the logic of interpretation. Assuming no interaction, a
categorical-predictors-only model, and aside from the intercept which
captures the mean for reference categories (in this case, boys in the
mixed schools), I have learned to interpret any main effect coef for a
categorical predictor by thinking of that coef. as something that can
differ from its reference category to affect "y" ***holding any other
categorical predictor in the model at its reference category***.
By this logic, "schgendboy-only" main effect coef should mean diff.
bet. boys (held constant at the reference category) in boy-only vs.
mixed schools (which shows "schgendboy-only" can differ from its
reference category i.e, mixed schools).
By this logic, "sexgirls" main effect coef should mean diff. bet.
girls vs. boys (which shows "sexgirls" can differ from its reference
category i.e, boys) in mixed schools (held constant at the reference
category).
Therefore, by this logic, "schgendgirl-only" main effect coef should
mean diff. bet. boys (held constant at the reference category) in
girl-only vs. mixed schools (which shows "schgendgirl-only" can differ
from its reference category i.e, mixed schools).
My question is that is my logic of interpretation incorrect? Or are
there exceptions to my logic of interpretation of which interpreting
"schgendgirl-only" coef is one?
Thank you very much,
Simon
On Sun, Sep 26, 2021 at 12:00 AM Juho Kristian Ruohonen
<juho.kristian.ruohonen at gmail.com> wrote:
Fellow student commenting here...
As you suggest, schgendgirl-only can only ever apply to female
students. Strictly speaking, it's the estimated mean difference between a
student of any sex in a girls-only school and a similar student in a mixed
school. But since such comparisons are only observed between girls, the
estimate is necessarily informed by girl data only. So your intended
interpretation of the coefficient is correct.
su 26. syysk. 2021 klo 0.27 Simon Harmel (sim.harmel at gmail.com)
Dear Colleagues,
Apologies for crossposting (
I've two categorical moderators i.e., students' ***sex*** (`boys`,
`girls`) and the ***school-gender system*** (`boy-only`, `girl-only`,
`mixed`) in a model like: `y ~ sex + schoolgend`.
My coefs are below. I can interpret three of the coefs but wonder how
to interpret the third one from the top (.175)?
Assume "intrcpt" represents the boys' mean in mixed schools.
Estimate
(Intercept) -0.189
schgendboy-only 0.180
schgendgirl-only 0.175
sexgirls 0.168
My interpretations of the coefficients are as follows:
"(Intercept)": mean of y for boys in mixed schools =
"schgendboy-only": diff. bet. boys in boy-only vs. mixed schools =
"schgendgirl-only": diff. bet. ???????????????????????????? = +.175
"sexgirls": diff. bet. girls vs. boys in mixed
If my interpretation logic for all other coefs is correct, then, this
third coef. must mean:
diff. bet. boys in girl-only vs. mixed schools = +.175! (which makes
ps. I know I will end-up interpreting +1.75 as: diff. bet. girls in
girl-only vs. mixed schools BUT this doesn't follow the
logic for other coefs PLUS there are no labels in the output to show
what's what!
Many thanks,
Simon