I have a query re Blasnik's Law, first named in the Statalist archives
by Nick Cox at
http://www.stata.com/statalist/archive/2007-08/msg00668.html
which states that using the -in- qualifier uses less computing time than
the equivalent -if- qualifier. For instance
regress mpg weight in 53/74
uses less time than
regress mpg weight if _n>=53 & _n<=74
because Stata does not have to check every observation in the dataset in
memory the first way, but has to do so the second way. My query is: Does
Blasnik's Law apply to the -use- command? That is to say, does the
statement
use mybigdata.dta in 3959/4030
use much less computing time than the statement
use mybigdata.dta if _n>=3959 & _n<=4030
which should input the same data into the memory? I ask because, as I
understand it, Stata datasets are sequential-access files (unlike SAS
datasets which I understand are random-access, with the option of having
multiple indices), and this should imply that Stata has to read through
observations 1 to 3958 before reading observation 3959.
My motivation is that I wish to streamline the command -parmby-, which
currently processes multiple by-groups by inputting the whole dataset
repeatedly, using the -restore, preserve- command, and then dropping all
by-groups except one. I am trying to think of a better way.
Best wishes (and thanks in advance)
Roger
Roger Newson
Lecturer in Medical Statistics
Respiratory Epidemiology and Public Health Group
National Heart and Lung Institute
Imperial College London
Royal Brompton campus
Room 33, Emmanuel Kaye Building
1B Manresa Road
London SW3 6LR
UNITED KINGDOM
Tel: +44 (0)20 7352 8121 ext 3381
Fax: +44 (0)20 7351 8322
Email: [email protected]
Web page: www.imperial.ac.uk/nhli/r.newson/
Departmental Web page:
http://www1.imperial.ac.uk/medicine/about/divisions/nhli/respiration/pop
genetics/reph/
Opinions expressed are those of the author, not of the institution.
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