Re: st: Bootstrapping: Comparing the difference between means

[Nick Cox <njcoxstata@gmail.com>]

I don't see that you need to write a program here.

sysuse auto
bootstrap (r(mu_1) - r(mu_2)), reps(10000) nowarn nodots :  ttest mpg,
by(foreign)

What are you doing wrong?

You don't mention starting with the on-line help and manual entry. The
very first example shows that you can calculate the results of
expressions containing different saved results on the fly with the
-bootstrap- command.

... if (del==1) + (del==2) should give the right result, but it's
better style to use logical operators.

simulate diffa_1=r(mu_1) diffa_2 = (r(mu_2), reps(100) : the
parentheses aren't balanced.

Nick

On 3 April 2013 17:22, Fleming, Fiona M <f.fleming@imperial.ac.uk> wrote:

> I am hoping someone can help! I have been trying to work out, all day, how I can perform a bootstrap on the mean difference of two samples. I have scoured the Statalist, FAQ etc to get ideas and have recently been  trying to replicate the programming and commands illustrated in Example 2 on http://statistics.ats.ucla.edu/stat/stata/faq/ownboot.htm  with my own data set i.e.:
>
> // step 1
> ttest dcp  if (del==1) + (del==2), by(del)
> return list
> matrix mu = (r(mu_1), r(mu_2))
> matrix list mu
>
> // step 2
> capture program drop mydiffa
> program define mydiffa, rclass
> preserve
> bsample
> ttest dcp if (del==1) + (del==2), by(del)
> estat mu
> return scalar diffa_1 = r(mu_1)
> return scalar diffa_2 = r(mu_2)
> restore
> end
>
> // step 3
> simulate diffa_1=r(mu_1) diffa_2 = (r(mu_2), reps(100) seed(12345): mydiffa
> bstat, stat (mu) n(200)
> estat bootstrap, all
>
> after running this 'simulate' I get the following error and cannot proceed-
> '' found where ':' expected
> r(198);
>
>
> Please could you offer any advice as to what I am doing wrong?
>
> In addition, what I have written above will only give me the bootstrap SE and CI for each of the means and not the difference of the means, if you have any further advice on how I might run that I would be extremely grateful.

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