Re: st: RE: Linear regression of 'log' predictors

 From Richard Goldstein To statalist@hsphsun2.harvard.edu Subject Re: st: RE: Linear regression of 'log' predictors Date Wed, 27 Sep 2006 10:20:21 -0400

```Maarten Buis wrote:

```
```Ashwin:
```
```[snip]
```
```As for interpretation, say you have one explanatory variable called female (0 = male, 1 = female) and you find a regression coefficient of -4, than the average duration is 4% less for females than for males.
```
```actually, this is not correct -- see the -logdummy- command and writeup

Rich

```
HTH,
Maarten

-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology Vrije Universiteit Amsterdam Boelelaan 1081 1081 HV Amsterdam The Netherlands

Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715

http://home.fsw.vu.nl/m.buis/
-----------------------------------------

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of Ashwin Ananthakrishnan
Sent: woensdag 27 september 2006 15:32
To: statalist@hsphsun2.harvard.edu
Subject: st: Linear regression of 'log' predictors

I have a model where the outcome is length of stay
(los). This variable has some right skew and is not
perfectly 'normal'.

Is it valid for me to run linear regression of other
predictors on length of stay if the los is not
normally distributed?

If it is not valid, then log (los) is a normally
distributed variable. But how do I interpret the
coefficients of the log(los). I find that
exponentiating log(los) coefficient doesn't seem to be
appropriate as it doesn't yield valid results. For
example p>0.05, but the 95% CI don't overlap 'zero'
which is what I would expect in linear regression.
Also exp(log(los)) doesn't give a similar estimate as
the coefficients if I run the regression on los
directly.

I apologize in advance if my question is either to
basic or difficult to understand.
Thank you.
```*
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