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st: New versions of -parmest- and -ingap- on SSC

From   "Newson, Roger B" <>
To   statalist <>
Subject   st: New versions of -parmest- and -ingap- on SSC
Date   Thu, 23 Apr 2009 13:17:58 +0100

Thanks to Kit Baum, new versions of the -parmest- and -ingap- packages are now available for download from SSC. In Stata, use the -ssc- command to do this, or use -adoupdate- if you already have a version of the package.

The -parmest- and -ingap- pachages are described as below on my website.

In the new -parmest- version, the -parmcip-, -parmest-, -parmby- and -metaparm- modules now all produce confidence limit variables with a characteristic named -varname[level]-, containing the numeric percentage confidence level used in calculating the confidence limits. This is intended as an aid for programmers, who may wish to re-label variables, or re-format output, to conform with non-standard presentation styles, or even languages other than English.

The new -ingap- package has now been updated to Stata Version 10. Also, the -rstring()- option, used to fill in string variables in gap observations, has been extended to fill them in with a wider range of variable attributes, which may now be the variable's order, name, storage type, display format, or a variable characteristic.

Users of Stata Versions 7, 8 and 9 can still download the old Stata 7 version of -ingap- from my website by typing, in Stata,
net from "";
and selecting and downloading -ingap-. Similarly, users can still download the Stata 9, 8, 7, 6 and 5 versions of -parmest- from my website by typing, in Stata,
net from "";
and selecting the sub-directory corresponding to the user's version of Stata.

Best wishes


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.

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: 22april2009
      Stata-Version: 10

INSTALLATION FILES                                  (click here to install)
(click here to return to the previous screen)

package ingap from

      ingap: Insert gap observations in a dataset

      ingap inserts gap observations into a list of positions in an existing data
      set. All existing variables in the dataset will have missing values in the
      gap observations, unless the user specifies otherwise.  Often, the user
      specifies non-missing values in the gap observations for one particular
      existing string variable, known as the row label variable. This row label
      variable may then be output with a list of other variables to form a
      publication-ready table with labelled gap rows, using the listtex package.
      Alternatively, the row label variable may be encoded, using the sencode
      package, to form a numeric variable with value labels. This numeric variable
      can then be plotted on one axis of a graph to define axis labels, including
      gap axis labels.  The sencode and listtex packages are downloadable from SSC
      or from this website.
      Author: Roger Newson
      Distribution-Date: 22april2009
      Stata-Version: 10

INSTALLATION FILES                                  (click here to install)
(click here to return to the previous screen)

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