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st: New version of -parmest- on SSC
From
"Roger B. Newson" <[email protected]>
To
"[email protected]" <[email protected]>
Subject
st: New version of -parmest- on SSC
Date
Fri, 12 Oct 2012 17:16:29 +0100
Thanks once again to Kit Baum, a new version of the -parmest- package is
now available for download from SSC. In Stata, use the -ssc- command to
do this, or -adoupdate- if you already have an old version of -parmest-.
The -parmest- package is described as below on my website. In the new
version, all 4 modules of the package (-parmcip-, -metaparm-, -parmest-
and -parmby-) now have the new options -mcompare()- to select a
multiple-comparisons method for adjustting the confidence limits and the
P-values, and a -mcomci()- option to select a multiple-comparison method
for adjusting the confidence limits only. Both of these options may have
values -noadjust- (the default ), -bonferroni- (specifying the
Bonferroni adjustment), or -sidak- (specifying the Sidak adjustment).
Users who want to adjust the P-values and not the confidence limits, or
even to use different methods to adjust the P-values and the confidence
limits, are advised to use the -qqvalue- package, which you can also
download from SSC.
Best wishes
Roger
-------------------------------------------------------------------------------------
package parmest from http://www.imperial.ac.uk/nhli/r.newson/stata11
-------------------------------------------------------------------------------------
TITLE
parmest: Create datasets with 1 observation per estimated parameter
DESCRIPTION/AUTHOR(S)
The parmest package has 4 modules: parmest, parmby, parmcip and
metaparm.
parmest creates an output dataset, with 1 observation per
parameter of the
most recent estimation results, and variables corresponding to
parameter names,
estimates, standard errors, z- or t-test statistics, P-values,
confidence
limits and other parameter attributes. parmby is a quasi-byable
extension to
parmest, which calls an estimation command, and creates a new
dataset, with 1
observation per parameter if the by() option is unspecified, or 1
observation
per parameter per by-group if the by() option is specified.
parmcip inputs
variables containing estimates, standard errors and (optionally)
degrees of
freedom, and computes new variables containing confidence
intervals and
P-values. metaparm inputs a parmest-type dataset with 1
observation for each
of a set of independently-estimated parameters, and outputs a
dataset with
1 observation for each of a set of linear combinations of these
parameters,
with confidence intervals and P-values, as for a meta-analysis.
The output
datasets created by parmest, parmby or metaparm may be listed to
the Stata
log and/or saved to a file and/or retained in memory (overwriting any
pre-existing dataset). The confidence intervals, P-values and
other parameter
attributes in the dataset may be listed and/or plotted and/or
tabulated.
Author: Roger Newson
Distribution-Date: 12 October2012
Stata-Version: 11
INSTALLATION FILES (click here to install)
metaparm.ado
parmby.ado
parmcip.ado
parmest.ado
metaparm.sthlp
metaparm_content_opts.sthlp
metaparm_outdest_opts.sthlp
metaparm_resultssets.sthlp
parmby.sthlp
parmby_only_opts.sthlp
parmcip.sthlp
parmcip_opts.sthlp
parmest.sthlp
parmest_ci_opts.sthlp
parmest_outdest_opts.sthlp
parmest_resultssets.sthlp
parmest_varadd_opts.sthlp
parmest_varmod_opts.sthlp
-------------------------------------------------------------------------------------
(click here to return to the previous screen)
--
Roger B Newson BSc MSc DPhil
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: http://www.imperial.ac.uk/nhli/r.newson/
Departmental Web page:
http://www1.imperial.ac.uk/medicine/about/divisions/nhli/respiration/popgenetics/reph/
Opinions expressed are those of the author, not of the institution.
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