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st: New version of -parmest- on SSC

From   "Roger B. Newson" <>
To   "" <>
Subject   st: New version of -parmest- on SSC
Date   Thu, 27 Sep 2012 19:24:09 +0100

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


package parmest from

      parmest: Create datasets with 1 observation per estimated parameter

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)
(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
Tel: +44 (0)20 7352 8121 ext 3381
Fax: +44 (0)20 7351 8322
Web page:
Departmental Web page:

Opinions expressed are those of the author, not of the institution.
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