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Re: st: logit transformation of RHS variable

 From Richard Williams To statalist@hsphsun2.harvard.edu, statalist@hsphsun2.harvard.edu Subject Re: st: logit transformation of RHS variable Date Wed, 04 Jan 2012 22:35:40 -0500

```At 08:25 PM 1/4/2012, Brendan Halpin wrote:
```
```On Wed, Jan 04 2012, Raymond Lim wrote:

> Hello Statalisters,
> I have an independent variable that I believe that needs to be
> transformed because it's bounded between 0 and 1, and it's easier to
> go from 0 to .10 than say .80 to .90. My question is, can I use a
> logit transformation on this RHS variable (new_x = x / (1 - x)? Or are
> logits usually for LHS variables only?

I'd read the logit transformation as suggesting it is harder rather than
easier to go from 0 to 0.1 than from 0.8 to 0.9. In log-odds 0 is
-infinity and 0.1 is log(0.1111) or about -2.2, whereas 0.8 to 0.9 is
1.4 to 2.2. The logit makes it hard to move at both extremes, but easy
around 0.5.

It may be that the "fractional logit model" may be what you need:

glm y x1 x2 ... , family(binomial) link(logit) robust

Googling "fractional logit" gets
www.maartenbuis.nl/presentations/UKsug06.pdf as the first hit. Maarten
may have more to say himself, but I would imagine he is currently
asleep!
```
```
```
I don't think fractional logit applies here since he is talking about transforming an independent rather than dependent variable.
```

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Richard Williams, Notre Dame Dept of Sociology
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