st: New version of -parmest- on SSC

["Roger B. Newson" <r.newson@imperial.ac.uk>]

Thanks as always to the unfailing services of 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, the -dfcombine()- option of the -metaparm- module, which 
specifies how to combine input degrees of freedom to compute output 
degrees of freedom for a linear combination of independent parameters 
(eg in a meta-analysis or for a pairwise difference), has been upgraded 
with a new possible value -welch-, in addition to the existing 
possibilities -satterthwaite- and -constant-. The -dfcombine- option can 
now also be abbreviated to the forst 1 or more letters, as in 
-dfcombine(w)- for -dfcombine(welch)-.

Best wishes

Roger


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package parmest from http://www.imperial.ac.uk/nhli/r.newson/stata11
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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: 24september2012
      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
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(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: r.newson@imperial.ac.uk
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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