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Re: st: Log Normality of Dependentvar


From   sjsamuels@gmail.com
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Log Normality of Dependentvar
Date   Mon, 8 Jun 2009 12:38:35 -0400

-Chris--

-lnskew0-- finds  by iteration a value of k for which y= ln(x - k) has
skewness zero.  The manual implies that with the "lnnormal" option,
-swilk- , estimates "k" by the method of -lnskew0-.  In fact, the ado
file for -swilk- does not call -lnskew0-, but instead computes an
approximation.. This probably accounts for the discrepancy that you
observed.

Analyses of  ln(var) and of the transformation  -bcskew0- are
irrelevant to -swilk-, because the 'lnnormal" option considers the
hypothesis of a three-parameter lognormal distribution.   I presume
that by "skskew0"  you meant  "lnskew0

-Steve

On Mon, Jun 8, 2009 at 6:18 AM, Maarten buis<maartenbuis@yahoo.co.uk> wrote:
>
> --- On Mon, 8/6/09, Christian Weiss wrote:
>> testing my dependent var via swilk or sfrancia rejects the
>> Null Hypothesis of Normality.
>
> This is problematic for a number of reasons:
>
> 1) Regression never assumes that the dependent variable is
> normally distributed, except when you have no explanatory
> variables. It only assumes that the residuals are normally
> distributed.
>
> 2) Testing for the normality of the residuals should only
> be done once you are confinced that the other assumptions
> have been met, as violations of the other assumptions are
> likely to lead to residuals that look non-normal
>
> 3) The normality of the residuals is probably the least
> important of the regression assumptions, as regression
> is reasonably robust to violations of it.
>
> 4) Tests are probably not the best way to assess whether
> the errors are normaly distributed. Graphical inspection
> is usually more informative and powerful, see:
> -help diagnostic plots- and -ssc d hangroot- for tools
> to help with that.
>
> For a more general set of tools to perform post-estimation
> checks of  regression assumptions see:
> -help regress postestimation-.
>
>

On Mon, Jun 8, 2009 at 5:38 AM, Christian
Weiss<christian.weiss@nightberry.de> wrote:
>
> testing my dependent var via swilk or sfrancia rejects the Null
> Hypothesis of Normality.
> However, using the "lnnormal" option of swilk accepts the nully
> hypothesis - it seems that the dependent variable is lognormal
> distributed.
>
>
> Suprisingly,after transformim my dependent variable by ln(var) or by
> skskew0 / bcskew0, swilk still rejects the null hypothesis of
> normality.
>
> How can that be explained?
>
> ..puzzled...Chris
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