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st: New versions of -regpar-, -punaf- and -punafcc- on SSC


From   "Roger B. Newson" <r.newson@imperial.ac.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: New versions of -regpar-, -punaf- and -punafcc- on SSC
Date   Mon, 05 Dec 2011 11:10:09 +0000

Thanks once again to Kit Baum, new versions of the -regpar-, -punaf- and -punafcc- 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 packages -regpar-, -punaf- and -punafcc- are described as below on my website, and form a suite of programs (together with -margprev- and -marglmean-) for estimating attributable and unattributable risks and fractions and other scenario comparisons from cohort, cross-sectional, case-control and survival data. The new versions add an option -noesample-, functioning as the option of the same name for -margins-, and allowing the user to calculate out-of-sample scenario comparisons. For instance, we might fit a logistic regression model to a set of data, regressing disease rates with respect to gender, age and smoking, and then estimate population attributable risks and fractions for smoking standardized to a standard distribution of gender and age using that logistic regression model on a dataset representing a standard population.

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

TITLE
      regpar: Population attributable risks from binary regression models

DESCRIPTION/AUTHOR(S)
      regpar calculates confidence intervals for population attributable
      risks, and also for scenario proportions.  regpar can be used after
      an estimation command whose predicted values are interpreted as
      conditional proportions, such as logit, logistic, probit, or glm.
      It estimates two scenario proportions, a baseline scenario
      ("Scenario 0") and a fantasy scenario ("Scenario 1"), in which one
      or more exposure variables are assumed to be set to particular
      values (typically zero), and any other predictor variables in the
      model are assumed to remain the same.  It also estimates the
      difference between the Scenario 0 proportion and the Scenario 1
      proportion.  This difference is known as the population
      attributable risk (PAR), and represents the amount of risk
      attributable to living in Scenario 0 instead of Scenario 1.

      Author: Roger Newson
      Distribution-Date: 29november2011
      Stata-Version: 12

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

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

TITLE
      punaf: Population attributable fractions for cohort studies

DESCRIPTION/AUTHOR(S)
      punaf calculates confidence intervals for population attributable
      fractions, and also for scenario means and their ratio, known as
      the population unattributable fraction.  punaf can be used after
      an estimation command whose predicted values are interpreted as
      conditional arithmetic means, such as logit, logistic, poisson,
      or glm.  It estimates the logs of two scenario means, the
      baseline scenario ("Scenario 0") and a fantasy scenario
      ("Scenario 1"), in which one or more exposure variables are
      assumed to be set to particular values (typically zero), and any
      other predictor variables in the model are assumed to remain the
      same.  It also estimates the log of the ratio of the Scenario 1
      mean to the Scenario 0 mean.  This ratio is known as the
      population unattributable fraction, and is subtracted from 1 to
      derive the population attributable fraction, defined as the
      proportion of the mean of the outcome variable attributable to
      living in Scenario 0 instead of Scenario 1.

      Author: Roger Newson
      Distribution-Date: 29november2011
      Stata-Version: 12

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

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

TITLE
punafcc: Population attributable fractions for case-control and survival studies

DESCRIPTION/AUTHOR(S)
      punafcc calculates confidence intervals for population attributable
      and unattributable fractions in case-control or survival studies.
      punafcc can be used after an estimation command whose parameters are
      interpreted as log rate ratios, such as logit or logistic for
      case-control data, or stcox for survival data.  It estimates the log
      of the mean rate ratio, in cases or deaths, between 2 scenarios, a
      baseline scenario ("Scenario 0") and a fantasy scenario ("Scenario
      1"), in which one or more exposure variables are assumed to be set
      to particular values (typically zero), and any other predictor
      variables in the model are assumed to remain the same.  This ratio
      is known as the population unattributable fraction (PUF), and is
      subtracted from 1 to derive the population attributable fraction
      (PAF), defined as the proportion of the cases or deaths attributable
      to living in Scenario 0 instead of Scenario 1.

      Author: Roger Newson
      Distribution-Date: 29november2011
      Stata-Version: 12

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