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st: New versions of -margprev- and -marglmean- for SSC


From   "Roger B. Newson" <r.newson@imperial.ac.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: New versions of -margprev- and -marglmean- for SSC
Date   Mon, 28 Nov 2011 22:02:21 +0000

Thanks as always to Kit Baum, new versions of the -margprev- and -marglmean- packages are now available for download from SSC. In Stata, use the -ssc- command to do this, or -adoupdate- if you already have old versions of these packages.

The -margprev- and -marglmean- packages are described as below on my website. They are front-ends for -margins-, allowing the user to calculate confidence intervals for marginal prevalences and marginal arithmetic means, respectively, using the Normalizing and variance-stabilizing logit and log transformations, respectively. The new versions add an option -noesample-, functioning as the function of the same name for -margins-, and allowing the user to estimate out-of-sample marginal prevalences and means. For instance, we might fit logit or log-linear models to data for our own sample, and then load a dataset representing a standard population, and estimate marginal prevalences or means for that standard population. As an example, I have used -margprev- to standardize disease prevalences from the centres of a multi-centre European study to a European standard population with standard numbers for each age group and gender, to show to the reader that the differences in disease prevalence between centres are not artefacts of differences in gender and/or age distribution between centres.

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 margprev from http://www.imperial.ac.uk/nhli/r.newson/stata12
---------------------------------------------------------------------------

TITLE
      margprev: Marginal prevalences from binary regression models

DESCRIPTION/AUTHOR(S)
      margprev calculates confidence intervals for marginal
      prevalences, also known as scenario proportions.  margprev can be
      used after an estimation command whose predicted values are
      interpreted as conditional proportions, such as logit, logistic,
      probit, or glm.  It estimates a marginal prevalence for a
      scenario ("Scenario 1"), in which one or more predictor variables
      may be assumed to be set to particular values, and any other
      predictor variables in the model are assumed to remain the same.

      Author: Roger Newson
      Distribution-Date: 24november2011
      Stata-Version: 12

INSTALLATION FILES                                  (click here to install)
      margprev.ado
      margprev_p.ado
      margprev.sthlp
---------------------------------------------------------------------------
(click here to return to the previous screen)

---------------------------------------------------------------------------
package marglmean from http://www.imperial.ac.uk/nhli/r.newson/stata12
---------------------------------------------------------------------------

TITLE
      marglmean: Marginal log means from regression models

DESCRIPTION/AUTHOR(S)
      marglmean calculates symmetric confidence intervals for log
      marginal means (also known as log scenario means), and
      asymmetric confidence intervals for the marginal means
      themselves.  marglmean can be used after an estimation
      command whose predicted values are interpreted as positive
      conditional arithmetic means of non-negative-valued outcome
      variables, such as logit, logistic, probit, poisson, or glm
      with most non-Normal distributional families.  It can
      estimate a marginal mean for a scenario ("Scenario 1"), in
      which one or more exposure variables may be assumed to be
      set to particular values, and any other predictor variables
      in the model are assumed to remain the same.

      Author: Roger Newson
      Distribution-Date: 25november2011
      Stata-Version: 12

INSTALLATION FILES                                  (click here to install)
      marglmean.ado
      marglmean_p.ado
      marglmean.sthlp
---------------------------------------------------------------------------
(click here to return to the previous screen)
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