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RE: st: qnorm

 From amir gahremanpour To statalist Subject RE: st: qnorm Date Mon, 5 Mar 2012 10:14:58 -0600

```Nick and Maarten,

Thank you all so much for your compelling answers and explanations. I am glad I decided to bring these questions about normality and qnorm to this website. I always learn alot here, I like to call it  "stata-free university" !

best regards

Amir

> From: n.j.cox@durham.ac.uk
> To: statalist@hsphsun2.harvard.edu
> Date: Mon, 5 Mar 2012 15:23:52 +0000
> Subject: RE: st: qnorm
>
> The approach in Maarten's program is to generate a number of random samples and show the lot as replicates.
>
> Here as an alternative is some example code for individual 95% confidence intervals for each plotted point. -qplot- used at the end is from SJ. The code isn't smart about missing values, but it could easily be made smarter. I also guess the code could be shortened in the middle.
>
> sysuse auto, clear
>
> mata
> y = sort(st_data(., "mpg"), 1)
> mean = mean(y)
> sd = sqrt(variance(y))
> n = rows(y)
>
> compare = J(n, 0, .)
>
> for (j = 1; j <= 100; j++) {
> compare = compare, sort(rnormal(n, 1, mean, sd), 1)
> }
>
> envelope = J(n, 2, .)
> for (i = 1; i <= n; i++) {
> x = sort(compare[i,]', 1)
> envelope[i,] = ((x[2] + x[3])/2, (x[97] + x[98])/2)
> }
>
> names = tokens("_lower _upper")
> st_store(., names, envelope)
>
> end
>
> qplot mpg _lower _upper, ms(O i i) c(. J J) legend(off) ytitle("`: var label mpg'")
>
> Nick
> n.j.cox@durham.ac.uk
>
> Maarten Buis
>
> On Mon, Mar 5, 2012 at 10:03 AM, Nick Cox wrote:
> > 1. Simulate several samples from a distribution with the same mean and
> > standard deviation (or more generally an appropriate mean and standard
> > deviation) and use the resulting portfolio of plots in assessing what
> > kind of variability is to be expected.
>
> An easy way to do so is to use the -margdistfit- package, which you
> can install by typing in Stata -ssc install margdistfit-. The default
> is actually to first sample the mean and the standard deviation from
> its sampling distribution and than sample a new variable with those
> sampled means and standard deviation. I suspect that this makes sense
> in most cases, though I also suspect that it won't matter much. If you
> want to do exactly what Nick proposes you can add the -noparsamp-
> option.
>
> Here is an example of what such a graph would look like:
>
> *-------- begin example -----------
> sysuse auto, clear
> reg mpg
> margdistfit, qq name(qq)
> margdistfit, pp name(pp)
> margdistfit, hangroot name(hangr)
> margdistfit, cumul name(cumul)
> *--------- end example ------------
> (For more on examples I sent to the Statalist see:
> http://www.maartenbuis.nl/example_faq )
>
> Hope this helps,
> Maarten
>
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
>
> http://www.maartenbuis.nl
> --------------------------
> *
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>
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```