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st: New package -parmhet- on SSC


From   Roger Newson <r.newson@imperial.ac.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: New package -parmhet- on SSC
Date   Thu, 23 Sep 2010 16:01:09 +0100

Thanks to Kit Baum, a new package -parmhet- is now available for download from SSC. In Stata, use the -ssc- command to do this.

The -parmhet- package is described as below on my website, and is part of my "resultsset suite" of programs. It computes heterogeneity test statistics and (optionally) inverse-variance weights and Cochrane semi-weights in resultssets produced by the SSC package -parmest-. -parmhet- can be used with the -metaparm- module of -parmest- to implement fixed-effect meta-analysis, DerSimonian-Laird randomly-variable-effect meta-analysis, nonrandomly-variable-effect meta-analysis, and interaction tests, saving the results to a new resultsset, which can then be input to other resultsset-processing packages to produce plots and tables. This resultsset-based method for meta-analyses (and interaction tests) is designed to be more flexible even than -metan-, at the cost of having to know some Stata programming.

Best wishes

Roger


--
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.

---------------------------------------------------------------------------
package parmhet from http://www.imperial.ac.uk/nhli/r.newson/stata10
---------------------------------------------------------------------------

TITLE
      parmhet: Heterogeneity tests in parmest resultssets

DESCRIPTION/AUTHOR(S)
      parmhet and parmiv are designed for use with parmest resultssets,
      which have one observation per estimated parameter and data on
      parameter estimates.  parmhet inputs variables containing parameter
      estimates, standard errors and (optionally) degrees of freedom, and
      outputs an output dataset (or resultsset) with one observation, or
      one observation per by-group, and data on heterogeneity test
      statistics on the input parameters in the dataset or by-group.  The
      output dataset can be listed to the Stata log, saved to a disk file,
      or written to memory, overwriting the existing dataset.  Optionally,
      parmhet may also add variables to the existing dataset, containing
      inverse-variance weights and/or semi-weights and/or
      semi-weight-based standard errors.  These additional variables may
      then be input to the metaparm module of the parmest package, to
      produce summary meta-analysed parameter estimates, using the
      fixed-effect method or the DerSimonian-Laird
      randomly-variable-effect method.  parmiv is a routine intended for
      use by programmers, and inputs variables containing estimates,
      standard errors and (optionally) degrees of freedom, and outputs
      additional variables in the existing dataset, containing
      inverse-variance weights and/or semi-weights and/or
      semi-weight-based standard errors and/or heterogeneity test
      statistics for the dataset or by-group.

      Author: Roger Newson
      Distribution-Date: 22september2010
      Stata-Version: 10

INSTALLATION FILES                                  (click here to install)
      parmhet.ado
      parmiv.ado
      parmhet.sthlp
      parmhet_basic_opts.sthlp
      parmhet_resultsset_opts.sthlp
      parmhet_hettest_opts.sthlp
      parmhet_resultsset.sthlp
      parmiv.sthlp

ANCILLARY FILES                                     (click here to get)
      parmhet_example1.dta
---------------------------------------------------------------------------
(click here to return to the previous screen)

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