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st: TeXnical query re SJ


From   "Newson, Roger B" <[email protected]>
To   <[email protected]>
Subject   st: TeXnical query re SJ
Date   Mon, 28 Jul 2008 12:27:10 +0100

Fellow Statalisters (especially Stata Journal (SJ) editors):

A TeXnical query re SJ LaTeX. What LaTeX symbol does SJ use to represent
the (increasingly popular) conditional independence symbol introduced by
Dawid (1979)? I ask because I cannot find it listed in Section 3.3 of
the LaTeX guide (Lamport, 1994), and an early SJ article (Becker and
Ichino, 2004) uses as a substitute the official LaTeX \bot symbol (which
is similar but not the same), but a more recent SJ article (Nannicini,
2007) uses something that appears more like the original Dawid symbol.
Do SJ authors need to know anything special and/or install extra fonts
in order to use this symbol?

Best wishes (and thanks in advance)

Roger


References

Becker SO, Ichino A. 2002. Estimation of average treatment effects based
on propensity scores. The Stata Journal 2(4): 358-377.

Dawid AP. 1979. Conditional independence in statistical theory. Journal
of the Royal Statistical Society Series B (Methodological),41(1): 1-31.

Lamport L. 1994. LaTeX: a document preparation system. 2nd Edition.
Addison-Wesley. Boston, Mass: Addison-Wesley.

Nannicini TS. 2007. Simulation-based sensitivity analysis for matching
estimators. The Stata Journal 7(3): 334-350.

Roger B 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.

-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Newson, Roger
B
Sent: 28 July 2008 09:36
To: [email protected]
Subject: RE: st: Statistical advice about multiple comparison...

You might like to look at the somersd package, downloadable from SSC.
The somersd package calculates confidence intervals for a wide range of
rank statistics (Kendall's tau, Somers' D, Harrell's c, and median
slopes, differences or ratios), and provides versions for clustered data
(such as matched pairs). And the package comes with a set of .pdf
manuals.

To download the somersd package within Stata, type

ssc desc somersd
ssc install somersd, replace

and to copy the manuals to the local folder, type

net get somersd.pdf
net get cendif.pdf
net get censlope.pdf

I hope this helps.

Best wishes

Roger 


Roger B 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.

-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of jverkuilen
Sent: 25 July 2008 23:52
To: [email protected]
Subject: RE: st: Statistical advice about multiple comparison...

Nonparametric tests tend to lose a lot of power when you have many ties
as you will have here. 

You may benefit from a model for discete ordinal data such as -ologit-.
However it is not set up for repeated measures analysis. You may find
-gllamm- helpful there. See http://gllamm.org. 

-----Original Message-----
From: "Yupa" <[email protected]>
To: "Statalist" <[email protected]>
Sent: 7/25/2008 6:04 PM
Subject: st: Statistical advice about multiple comparison...

Dear statalisters,

I have 9 test items and each item is scored ordinally 1 to 4 points 
(distance between points isn't equal).
The test is administered to two populations; in the first population 
each item is taken two times for each subject (at different ages). The 
second population served as reference.
Some of the test items show a ceiling effect (aren't able to 
discriminate at high end of the scale, and lower scores are not 
represented).
I have to compare the results of each item between the two timepoints of

the first population and between each timepoint of the first population 
versus the reference population.
I think that an equality test for matched data is adequate for the first

comparison (signrank) and an equality test for unmatched data (ranksum) 
for the second. 
Am I right or am I missing something?
May I analyze the data in a different way (different tests)?

Thanks in advance!
Francesco
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