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Re: st: St: z transformation - mibeta command


From   Nick Cox <njcoxstata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: St: z transformation - mibeta command
Date   Tue, 24 Apr 2012 09:31:11 +0100

I think for most people a z transformation suggests (value - mean) /
SD but a glance at -mibeta- (SSC) suggests that you want Fisher's z
transformation for Pearson correlations.

There is a tutorial at

SJ-8-3  pr0041  .  Speaking Stata: Corr. with confidence, Fisher's z revisited
        (help corrci, corrcii if installed) . . . . . . . . . . . .  N. J. Cox
        Q3/08   SJ 8(3):413--439
        reviews Fisher's z transformation and its inverse, the
        hyperbolic tangent, and reviews their use in inference
        with correlations

but if you use the software download the update from SJ-10-4 and note
that Stata as well as Mata now supports the trio -sinh()-, -cosh()-,
-tanh()-.

More generally: threads you start seem to move very slowly. See

http://blog.stata.com/2010/12/14/how-to-successfully-ask-a-question-on-statalist/

for some advice on making your questions clearer.

On Tue, Apr 24, 2012 at 9:04 AM, Hoang Dinh Quoc <hoangdquoc@gmail.com> wrote:

> I am looking for z transformation and mibeta command is supposed to create
> it but when I run this command it always reports no imputations.

Nick Cox

> If you have no missing values, you do not need to impute and indeed
> have no scope to impute what is not missing. In what sense is this a
> problem? It is simple good news.
>
> On Tue, Apr 24, 2012 at 8:29 AM, Hoang Dinh Quoc <hoangdquoc@gmail.com>

>> It does not work with other mi estimates such as mi estimate: reg y x1 x2
>> x3... and it reports the same 'no imputations'.
>>
>> I have no missing values in my dataset. Can this be the problem?

Richard Williams

>> At 11:36 PM 4/23/2012, Hoang Dinh Quoc wrote:

>>>When I used the command 'mibeta' in Stata for z transformation and I got a
>>>message stating 'no imputations'. Could anyone please tell me this
> problem?
>>>
>>>I converted my data into flong style (the command mi des tells 'Style:
>>>flong'.

>> My first guess would be that there is some sort of problem with your
>> imputations, but without seeing more of your code or output it is
>> impossible to tell. Do other mi estimate commands work, e.g. can you
>> do something like
>>
>> mi estimate: reg y x1 x2 x3
>>
>> without any problems?
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