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# Re: st: comparing coefficients

 From Richard Williams To statalist@hsphsun2.harvard.edu, statalist@hsphsun2.harvard.edu Subject Re: st: comparing coefficients Date Wed, 09 Jan 2013 20:02:11 -0500

```At 07:07 AM 1/9/2013, David Hoaglin wrote:
```
```John,

What's wrong with including both genders in a single model and
expanding the list of predictors to include gender and the interaction
of gender with each of the current predictors?
```
```
Actually, that has some problems of its own. Suppose you ran

use "http://www.indiana.edu/~jslsoc/stata/spex_data/ordwarm2.dta";, clear
reg warm i.yr89 i.white c.age c.ed if male==0
reg warm i.yr89 i.white c.age c.ed if male==1
reg warm i.male##(i.yr89 i.white c.age c.ed)

```
It isn't hard to see that the last model with interactions gives you the exact same results as the 2 groups run separately. Things are just parameterized differently.
```
But if instead you run

ologit warm i.yr89 i.white c.age c.ed if male==0, nolog
ologit warm i.yr89 i.white c.age c.ed if male==1, nolog
ologit warm i.male##(i.yr89 i.white c.age c.ed), nolog

```
You see the final model does not give exactly the same results as the first two models.
```
```
Why not? In the final ologit model, you are allowing all the variables to have different effects in each group. BUT, you are constraining the cut points to be the same for each group, whereas when you run the model separately for the two groups the cutpoints can differ. That may not be a bad assumption to make, but nonetheless it is an assumption.
```
```
Probably more important problems are outlined at http://www3.nd.edu/~rwilliam/xsoc73994/L31.pdf. The key issue is that, unless the two groups have the same residual variability, tests of equality across groups are distorted.
```
```
The more I work with ordinal models, the more I think you should do everything you can to get continuous dependent variables. There are a lot of things you can do in OLS regression that don't generalize as you would expect to logit and ologit models.
```
```
One other point: as far as I know this command from the original post is not legitimate, because there is no store option in ologit:
```
```
ologit y1 educationmedium educationhigh age income class household country if gender=0, or store(step1a)
```

```
```David Hoaglin

On Wed, Jan 9, 2013 at 4:30 AM, John Stymans <johnstymans@hotmail.be> wrote:
> Dear Statalist Users,
> I have a problem when comparing coefficients across groups.
> I am using Stata 12.
> I first run an ordered logit model for two groups (males and females).
>
```
> ologit y1 i.education age income class household country if gender=0, or store(step1a) > ologit y1 i.education age income class household country if gender=1, or store(step1b) > goal is to compare across gender the effect of education which is a categorical variable with 3 values, hence the use of i..
```>
> when I use suest:
>
> suest step1a step1b
>
> test [step1a _y1]i.education=[step1b_y1]i.education
>
```
> the command does not work. I am however able to split education in three values an add two of them to the regression (omitting educationlow);
```>
```
> ologit y1 educationmedium educationhigh age income class household country if gender=0, or store(step1a) > ologit y1 educationmedium educationhigh age income class household country if gender=1, or store(step1b)
```> and than run suest:
>
> suest step1a step1b
>
> test [step1a _y1]loweducation=[step1b_y1]loweducation
>
```
> Yet I am unable to compare the difference in significance of education across gender in general. Does anyone know how to solve this issue?
```>
> Many thanks in advance and best regards,
>
> John
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```
```
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Richard Williams, Notre Dame Dept of Sociology
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```

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