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Re: st: RE: ml and parmby versus statsby
From
Nick Cox <[email protected]>
To
[email protected]
Subject
Re: st: RE: ml and parmby versus statsby
Date
Wed, 12 Dec 2012 18:05:39 +0000
We can be pleased that you no longer see a problem, but what happened
remains mysterious.
1. -parmby- permits other options but these are in turn (if I follow
Roger's code correctly) passed to -parmest-, which does not in fact
allow a -quietly- option. So why your earlier code ran at all is a
puzzle.
2. In general, the effect of a -quietly- option in Stata would be that
something is done "quietly", although that's a convention, not a rule.
If so, results should be exactly as they were before, not different.
I spell out here, as we are all asked to do, that -parmby- is a
user-written command. I looked at -parmby- from SSC and -which- tells
me
*! Author: Roger Newson
*! Date: 02 September 2009
Nick
On Wed, Dec 12, 2012 at 5:41 PM, S. Suetens <[email protected]> wrote:
> This is very helpful.
> I re-ran the parmby command, but without including the quietly option, and estimation results are the same now as those under statsby.
Roger B. Newson
> I don't know how your -statsby- and -parmby- results are different, as you haven't told us. However, -statsby- creates a dataset with 1 observation per by-group, and different variables for the estimates and standard errors for different parameters. -parmby-, on the other hand, creates a dataset with 1 observation per parameter per by-group, with 1 variable for the estimate and 1 variable for the standard error, and other variables for the confidence limits and P-values.
>
> I am a bit mystified about the -quietly- option for -parmby-. As the author of -parmby-, I never knew that -parmby- had a -quietly- option, although it can take the -quietly- prefix like other Stata commands.
On 12/12/2012 15:52, S. Suetens wrote:
>> Is there anyone who can explain why maximum likelihood estimation gives different results under parmby as compared to statsby?
>> I have run the two commands below (based on the same likelihood function) and they give very different parameter estimates and standard errors.
>>
>> statsby _b _se, by(id) saving("D:\Statsby.dta", replace) nodots: ml
>> model lf MaxLik (lambda: strategy =) (rhosigma: RHO SIGMA, nocons),
>> max difficult
>>
>> parmby "ml model lf MaxLik (lambda: strategy =) (rhosigma: RHO SIGMA,
>> nocons), max difficult", by(id) saving("D:\Parmby.dta", replace)
>> quietly
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