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st: New versions of -punaf-, -punafcc-, -regpar-, -marglmean- and -margprev- 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 -punaf-, -punafcc-, -regpar-, -marglmean- and -margprev- on SSC
Date   Tue, 01 Oct 2013 11:44:00 +0100

Thanks yet again to Kit Baum, new versions of the -punaf-, -punafcc-, -regpar-, -marglmean- and -margprev- 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 -punaf-, -punafcc-, -regpar-, -marglmean- and -margprev- packages are described as below on my website, and are front ends for -margins- and -nlcom- for estimating population unattributable and attributable risks and fractions, scenario arithmetic means and scenario prevalences, all with confidence limits. They were presented at the 2012 Stata User Meeting (Newson, 2012). The new versions are updated to Stata Version 13, and add a -df(#)- option, like those for -margins- and -nlcom- under Stata Version 13, to specify non-default degrees of freedom for calculating the confidence limits. I have also reformed the output format for the matrix of confidence intervals, which is now %9.0g (as used by -centile- in official Stata), instead of %10.0g (as before). I would like to thank Bill Gould of StataCorp for suggesting this change in the output format at the 2012 UK Stata User Meeting, to reduce the number of unnecessary decimal places in the output.

Users of Stata Versions 12 and 11 can still download the Stata Version 12 versions of -punaf-, -punafcc-, -regpar-, -marglmean- and -margprev-, and the Stata Version 11 version of -punaf-, from my website by typing, in Stata,

net from "http://www.imperial.ac.uk/nhli/r.newson/";

and selecting the subdirectory for the most recent Stata version of the appropriate package compatible with their versions of Stata.

Best wishes

Roger

References

Newson, R. B. 2012. Scenario comparisons: How much good can we do? Presented at the 18th United Kingdom Stata Users' Group Meeting, 13–14 September, 2012. Download from
http://ideas.repec.org/p/boc/usug12/01.html

--
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.

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: 25september2013
      Stata-Version: 13

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/stata13
---------------------------------------------------------------------------------------------

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: 25september2013
      Stata-Version: 13

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

---------------------------------------------------------------------------------------------
package regpar from http://www.imperial.ac.uk/nhli/r.newson/stata13
---------------------------------------------------------------------------------------------

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: 25september2013
      Stata-Version: 13

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

---------------------------------------------------------------------------------------------
package marglmean from http://www.imperial.ac.uk/nhli/r.newson/stata13
---------------------------------------------------------------------------------------------

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: 25september2013
      Stata-Version: 13

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

---------------------------------------------------------------------------------------------
package margprev from http://www.imperial.ac.uk/nhli/r.newson/stata13
---------------------------------------------------------------------------------------------

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: 25september2013
      Stata-Version: 13

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