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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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